PHP Text Analysis is a library for performing Information Retrieval (IR) and Natural Language Processing (NLP) tasks using the PHP language

MIT Introduction to Deep Learning (6.S191) Instructors: Alexander Amini and Ava Soleimany Course Information Summary Prerequisites Schedule Lectures Labs, Final Projects, Grading, and Prizes Software labs Gather.Town lab + Office Hour sessions Final project Paper Review Project Proposal Presentation Project Proposal Grading Rubric Past Project Proposal Ideas Awards + Categories Important Links and Emails Course Information Summary MIT's introductory course on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of deep learning algorithms and get practical experience in building neural networks in TensorFlow. Course concludes with a project proposal competition with feedback from staff and a panel of industry sponsors. Prerequisites We expect basic knowledge of calculus (e.g., taking derivatives), linear algebra (e.g., matrix multiplication), and probability (e.g., Bayes theorem) -- we'll try to explain everything else along the way! Experience in Python is helpful but not necessary. This class is taught during MIT's IAP term by current MIT PhD researchers. Listeners are welcome! Schedule Monday Jan 18, 2021 Lecture: Introduction to Deep Learning and NNs Lab: Lab 1A Tensorflow and building NNs from scratch Tuesday Jan 19, 2021 Lecture: Deep Sequence Modelling Lab: Lab 1B Music Generation using RNNs Wednesday Jan 20, 2021 Lecture: Deep Computer Vision Lab: Lab 2A Image classification and detection Thursday Jan 21, 2021 Lecture: Deep Generative Modelling Lab: Lab 2B Debiasing facial recognition systems Friday Jan 22, 2021 Lecture: Deep Reinforcement Learning Lab: Lab 3 pixel-to-control planning Monday Jan 25, 2021 Lecture: Limitations and New Frontiers Lab: Lab 3 continued Tuesday Jan 26, 2021 Lecture (part 1): Evidential Deep Learning Lecture (part 2): Bias and Fairness Lab: Work on final assignments Lab competition entries due at 11:59pm ET on Canvas! Lab 1, Lab 2, and Lab 3 Wednesday Jan 27, 2021 Lecture (part 1): Nigel Duffy, Ernst & Young Lecture (part 2): Kate Saenko, Boston University and MIT-IBM Watson AI Lab Lab: Work on final assignments Assignments due: Sign up for Final Project Competition Thursday Jan 28, 2021 Lecture (part 1): Sanja Fidler, U. Toronto, Vector Institute, and NVIDIA Lecture (part 2): Katherine Chou, Google Lab: Work on final assignments Assignments due: 1 page paper review (if applicable) Friday Jan 29, 2021 Lecture: Student project pitch competition Lab: Awards ceremony and prize giveaway Assignments due: Project proposals (if applicable) Lectures Lectures will be held starting at 1:00pm ET from Jan 18 - Jan 29 2021, Monday through Friday, virtually through Zoom. Current MIT students, faculty, postdocs, researchers, staff, etc. will be able to access the lectures during this two week period, synchronously or asynchronously, via the MIT Canvas course webpage (MIT internal only). Lecture recordings will be uploaded to the Canvas as soon as possible; students are not required to attend any lectures synchronously. Please see the Canvas for details on Zoom links. The public edition of the course will only be made available after completion of the MIT course. Labs, Final Projects, Grading, and Prizes Course will be graded during MIT IAP for 6 units under P/D/F grading. Receiving a passing grade requires completion of each software lab project (through honor code, with submission required to enter lab competitions), a final project proposal/presentation or written review of a deep learning paper (submission required), and attendance/lecture viewing (through honor code). Submission of a written report or presentation of a project proposal will ensure a passing grade. MIT students will be eligible for prizes and awards as part of the class competitions. There will be two parts to the competitions: (1) software labs and (2) final projects. More information is provided below. Winners will be announced on the last day of class, with thousands of dollars of prizes being given away! Software labs There are three TensorFlow software lab exercises for the course, designed as iPython notebooks hosted in Google Colab. Software labs can be found on GitHub: https://github.com/aamini/introtodeeplearning. These are self-paced exercises and are designed to help you gain practical experience implementing neural networks in TensorFlow. For registered MIT students, submission of lab materials is not necessary to get credit for the course or to pass the course. At the end of each software lab there will be task-associated materials to submit (along with instructions) for entry into the competitions, open to MIT students and affiliates during the IAP offering. This includes MIT students/affiliates who are taking the class as listeners -- you are eligible! These instructions are provided at the end of each of the labs. Completing these tasks and submitting your materials to Canvas will enter you into a per-lab competition. MIT students and affiliates will be eligible for prizes during the IAP offering; at the end of the course, prize-winners will be awarded with their prizes. All competition submissions are due on January 26 at 11:59pm ET to Canvas. For the software lab competitions, submissions will be judged on the basis of the following criteria: Strength and quality of final results (lab dependent) Soundness of implementation and approach Thoroughness and quality of provided descriptions and figures Gather.Town lab + Office Hour sessions After each day’s lecture, there will be open Office Hours in the class GatherTown, up until 3pm ET. An MIT email is required to log in and join the GatherTown. During these sessions, there will not be a walk through or dictation of the labs; the labs are designed to be self-paced and to be worked on on your own time. The GatherTown sessions will be hosted by course staff and are held so you can: Ask questions on course lectures, labs, logistics, project, or anything else; Work on the labs in the presence of classmates/TAs/instructors; Meet classmates to find groups for the final project; Group work time for the final project; Bring the class community together. Final project To satisfy the final project requirement for this course, students will have two options: (1) write a 1 page paper review (single-spaced) on a recent deep learning paper of your choice or (2) participate and present in the project proposal pitch competition. The 1 page paper review option is straightforward, we propose some papers within this document to help you get started, and you can satisfy a passing grade with this option -- you will not be eligible for the grand prizes. On the other hand, participation in the project proposal pitch competition will equivalently satisfy your course requirements but additionally make you eligible for the grand prizes. See the section below for more details and requirements for each of these options. Paper Review Students may satisfy the final project requirement by reading and reviewing a recent deep learning paper of their choosing. In the written review, students should provide both: 1) a description of the problem, technical approach, and results of the paper; 2) critical analysis and exposition of the limitations of the work and opportunities for future work. Reviews should be submitted on Canvas by Thursday Jan 28, 2021, 11:59:59pm Eastern Time (ET). Just a few paper options to consider... https://papers.nips.cc/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf https://papers.nips.cc/paper/2018/file/69386f6bb1dfed68692a24c8686939b9-Paper.pdf https://papers.nips.cc/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf https://science.sciencemag.org/content/362/6419/1140 https://papers.nips.cc/paper/2018/file/0e64a7b00c83e3d22ce6b3acf2c582b6-Paper.pdf https://arxiv.org/pdf/1906.11829.pdf https://www.nature.com/articles/s42256-020-00237-3 https://pubmed.ncbi.nlm.nih.gov/32084340/ Project Proposal Presentation Keyword: proposal This is a 2 week course so we do not require results or working implementations! However, to win the top prizes, nice, clear results and implementations will demonstrate feasibility of your proposal which is something we look for! Logistics -- please read! You must sign up to present before 11:59:59pm Eastern Time (ET) on Wednesday Jan 27, 2021 Slides must be in a Google Slide before 11:59:59pm Eastern Time (ET) on Thursday Jan 28, 2021 Project groups can be between 1 and 5 people Listeners welcome To be eligible for a prize you must have at least 1 registered MIT student in your group Each participant will only be allowed to be in one group and present one project pitch Synchronous attendance on 1/29/21 is required to make the project pitch! 3 min presentation on your idea (we will be very strict with the time limits) Prizes! (see below) Sign up to Present here: by 11:59pm ET on Wednesday Jan 27 Once you sign up, make your slide in the following Google Slides; submit by midnight on Thursday Jan 28. Please specify the project group # on your slides!!! Things to Consider This doesn’t have to be a new deep learning method. It can just be an interesting application that you apply some existing deep learning method to. What problem are you solving? Are there use cases/applications? Why do you think deep learning methods might be suited to this task? How have people done it before? Is it a new task? If so, what are similar tasks that people have worked on? In what aspects have they succeeded or failed? What is your method of solving this problem? What type of model + architecture would you use? Why? What is the data for this task? Do you need to make a dataset or is there one publicly available? What are the characteristics of the data? Is it sparse, messy, imbalanced? How would you deal with that? Project Proposal Grading Rubric Project proposals will be evaluated by a panel of judges on the basis of the following three criteria: 1) novelty and impact; 2) technical soundness, feasibility, and organization, including quality of any presented results; 3) clarity and presentation. Each judge will award a score from 1 (lowest) to 5 (highest) for each of the criteria; the average score from each judge across these criteria will then be averaged with that of the other judges to provide the final score. The proposals with the highest final scores will be selected for prizes. Here are the guidelines for the criteria: Novelty and impact: encompasses the potential impact of the project idea, its novelty with respect to existing approaches. Why does the proposed work matter? What problem(s) does it solve? Why are these problems important? Technical soundness, feasibility, and organization: encompasses all technical aspects of the proposal. Do the proposed methodology and architecture make sense? Is the architecture the best suited for the proposed problem? Is deep learning the best approach for the problem? How realistic is it to implement the idea? Was there any implementation of the method? If results and data are presented, we will evaluate the strength of the results/data. Clarity and presentation: encompasses the delivery and quality of the presentation itself. Is the talk well organized? Are the slides aesthetically compelling? Is there a clear, well-delivered narrative? Are the problem and proposed method clearly presented? Past Project Proposal Ideas Recipe Generation with RNNs Can we compress videos with CNN + RNN? Music Generation with RNNs Style Transfer Applied to X GAN’s on a new modality Summarizing text/news articles Combining news articles about similar events Code or spec generation Multimodal speech → handwriting Generate handwriting based on keywords (i.e. cursive, slanted, neat) Predicting stock market trends Show language learners articles or videos at their level Transfer of writing style Chemical Synthesis with Recurrent Neural networks Transfer learning to learn something in a domain for which it’s hard or risky to gather data or do training RNNs to model some type of time series data Computer vision to coach sports players Computer vision system for safety brakes or warnings Use IBM Watson API to get the sentiment of your Facebook newsfeed Deep learning webcam to give wifi-access to friends or improve video chat in some way Domain-specific chatbot to help you perform a specific task Detect whether a signature is fraudulent Awards + Categories Final Project Awards: 1x NVIDIA RTX 3080 4x Google Home Max 3x Display Monitors Software Lab Awards: Bose headphones (Lab 1) Display monitor (Lab 2) Bebop drone (Lab 3) Important Links and Emails Course website: http://introtodeeplearning.com Course staff: introtodeeplearning-staff@mit.edu Piazza forum (MIT only): https://piazza.com/mit/spring2021/6s191 Canvas (MIT only): https://canvas.mit.edu/courses/8291 Software lab repository: https://github.com/aamini/introtodeeplearning Lab/office hour sessions (MIT only): https://gather.town/app/56toTnlBrsKCyFgj/MITDeepLearning

W3C Strategic Highlights September 2019 This report was prepared for the September 2019 W3C Advisory Committee Meeting (W3C Member link). See the accompanying W3C Fact Sheet — September 2019. For the previous edition, see the April 2019 W3C Strategic Highlights. For future editions of this report, please consult the latest version. A Chinese translation is available. ☰ Contents Introduction Future Web Standards Meeting Industry Needs Web Payments Digital Publishing Media and Entertainment Web & Telecommunications Real-Time Communications (WebRTC) Web & Networks Automotive Web of Things Strengthening the Core of the Web HTML CSS Fonts SVG Audio Performance Web Performance WebAssembly Testing Browser Testing and Tools WebPlatform Tests Web of Data Web for All Security, Privacy, Identity Internationalization (i18n) Web Accessibility Outreach to the world W3C Developer Relations W3C Training Translations W3C Liaisons Introduction This report highlights recent work of enhancement of the existing landscape of the Web platform and innovation for the growth and strength of the Web. 33 working groups and a dozen interest groups enable W3C to pursue its mission through the creation of Web standards, guidelines, and supporting materials. We track the tremendous work done across the Consortium through homogeneous work-spaces in Github which enables better monitoring and management. We are in the middle of a period where we are chartering numerous working groups which demonstrate the rapid degree of change for the Web platform: After 4 years, we are nearly ready to publish a Payment Request API Proposed Recommendation and we need to soon charter follow-on work. In the last year we chartered the Web Payment Security Interest Group. In the last year we chartered the Web Media Working Group with 7 specifications for next generation Media support on the Web. We have Accessibility Guidelines under W3C Member review which includes Silver, a new approach. We have just launched the Decentralized Identifier Working Group which has tremendous potential because Decentralized Identifier (DID) is an identifier that is globally unique, resolveable with high availability, and cryptographically verifiable. We have Privacy IG (PING) under W3C Member review which strengthens our focus on the tradeoff between privacy and function. We have a new CSS charter under W3C Member review which maps the group's work for the next three years. In this period, W3C and the WHATWG have succesfully completed the negotiation of a Memorandum of Understanding rooted in the mutual belief that that having two distinct specifications claiming to be normative is generally harmful for the Web community. The MOU, signed last May, describes how the two organizations are to collaborate on the development of a single authoritative version of the HTML and DOM specifications. W3C subsequently rechartered the HTML Working Group to assist the W3C community in raising issues and proposing solutions for the HTML and DOM specifications, and for the production of W3C Recommendations from WHATWG Review Drafts. As the Web evolves continuously, some groups are looking for ways for specifications to do so as well. So-called "evergreen recommendations" or "living standards" aim to track continuous development (and maintenance) of features, on a feature-by-feature basis, while getting review and patent commitments. We see the maturation and further development of an incredible number of new technologies coming to the Web. Continued progress in many areas demonstrates the vitality of the W3C and the Web community, as the rest of the report illustrates. Future Web Standards W3C has a variety of mechanisms for listening to what the community thinks could become good future Web standards. These include discussions with the Membership, discussions with other standards bodies, the activities of thousands of participants in over 300 community groups, and W3C Workshops. There are lots of good ideas. The W3C strategy team has been identifying promising topics and invites public participation. Future, recent and under consideration Workshops include: Inclusive XR (5-6 November 2019, Seattle, WA, USA) to explore existing and future approaches on making Virtual and Augmented Reality experiences more inclusive, including to people with disabilities; W3C Workshop on Data Models for Transportation (12-13 September 2019, Palo Alto, CA, USA) W3C Workshop on Web Games (27-28 June 2019, Redmond, WA, USA), view report Second W3C Workshop on the Web of Things (3-5 June 2019, Munich, Germany) W3C Workshop on Web Standardization for Graph Data; Creating Bridges: RDF, Property Graph and SQL (4-6 March 2019, Berlin, Germany), view report Web & Machine Learning. The Strategy Funnel documents the staff's exploration of potential new work at various phases: Exploration and Investigation, Incubation and Evaluation, and eventually to the chartering of a new standards group. The Funnel view is a GitHub Project where new area are issues represented by “cards” which move through the columns, usually from left to right. Most cards start in Exploration and move towards Chartering, or move out of the funnel. Public input is welcome at any stage but particularly once Incubation has begun. This helps W3C identify work that is sufficiently incubated to warrant standardization, to review the ecosystem around the work and indicate interest in participating in its standardization, and then to draft a charter that reflects an appropriate scope. Ongoing feedback can speed up the overall standardization process. Since the previous highlights document, W3C has chartered a number of groups, and started discussion on many more: Newly Chartered or Rechartered Web Application Security WG (03-Apr) Web Payment Security IG (17-Apr) Patent and Standards IG (24-Apr) Web Applications WG (14-May) Web & Networks IG (16-May) Media WG (23-May) Media and Entertainment IG (06-Jun) HTML WG (06-Jun) Decentralized Identifier WG (05-Sep) Extended Privacy IG (PING) (30-Sep) Verifiable Claims WG (30-Sep) Service Workers WG (31-Dec) Dataset Exchange WG (31-Dec) Web of Things Working Group (31-Dec) Web Audio Working Group (31-Dec) Proposed charters / Advance Notice Accessibility Guidelines WG Privacy IG (PING) RDF Literal Direction WG Timed Text WG CSS WG Web Authentication WG Closed Internationalization Tag Set IG Meeting Industry Needs Web Payments All Web Payments specifications W3C's payments standards enable a streamlined checkout experience, enabling a consistent user experience across the Web with lower front end development costs for merchants. Users can store and reuse information and more quickly and accurately complete online transactions. The Web Payments Working Group has republished Payment Request API as a Candidate Recommendation, aiming to publish a Proposed Recommendation in the Fall 2019, and is discussing use cases and features for Payment Request after publication of the 1.0 Recommendation. Browser vendors have been finalizing implementation of features added in the past year (view the implementation report). As work continues on the Payment Handler API and its implementation (currently in Chrome and Edge Canary), one focus in 2019 is to increase adoption in other browsers. Recently, Mastercard demonstrated the use of Payment Request API to carry out EMVCo's Secure Remote Commerce (SRC) protocol whose payment method definition is being developed with active participation by Visa, Mastercard, American Express, and Discover. Payment method availability is a key factor in merchant considerations about adopting Payment Request API. The ability to get uniform adoption of a new payment method such as Secure Remote Commerce (SRC) also depends on the availability of the Payment Handler API in browsers, or of proprietary alternatives. Web Monetization, which the Web Payments Working Group will discuss again at its face-to-face meeting in September, can be used to enable micropayments as an alternative revenue stream to advertising. Since the beginning of 2019, Amazon, Brave Software, JCB, Certus Cybersecurity Solutions and Netflix have joined the Web Payments Working Group. In April, W3C launched the Web Payment Security Group to enable W3C, EMVCo, and the FIDO Alliance to collaborate on a vision for Web payment security and interoperability. Participants will define areas of collaboration and identify gaps between existing technical specifications in order to increase compatibility among different technologies, such as: How do SRC, FIDO, and Payment Request relate? The Payment Services Directive 2 (PSD2) regulations in Europe are scheduled to take effect in September 2019. What is the role of EMVCo, W3C, and FIDO technologies, and what is the current state of readiness for the deadline? How can we improve privacy on the Web at the same time as we meet industry requirements regarding user identity? Digital Publishing All Digital Publishing specifications, Publication milestones The Web is the universal publishing platform. Publishing is increasingly impacted by the Web, and the Web increasingly impacts Publishing. Topic of particular interest to Publishing@W3C include typography and layout, accessibility, usability, portability, distribution, archiving, offline access, print on demand, and reliable cross referencing. And the diverse publishing community represented in the groups consist of the traditional "trade" publishers, ebook reading system manufacturers, but also publishers of audio book, scholarly journals or educational materials, library scientists or browser developers. The Publishing Working Group currently concentrates on Audiobooks which lack a comprehensive standard, thus incurring extra costs and time to publish in this booming market. Active development is ongoing on the future standard: Publication Manifest Audiobook profile for Web Publications Lightweight Packaging Format The BD Comics Manga Community Group, the Synchronized Multimedia for Publications Community Group, the Publishing Community Group and a future group on archival, are companions to the working group where specific work is developed and incubated. The Publishing Community Group is a recently launched incubation channel for Publishing@W3C. The goal of the group is to propose, document, and prototype features broadly related to: publications on the Web reading modes and systems and the user experience of publications The EPUB 3 Community Group has successfully completed the revision of EPUB 3.2. The Publishing Business Group fosters ongoing participation by members of the publishing industry and the overall ecosystem in the development of Web infrastructure to better support the needs of the industry. The Business Group serves as an additional conduit to the Publishing Working Group and several Community Groups for feedback between the publishing ecosystem and W3C. The Publishing BG has played a vital role in fostering and advancing the adoption and continued development of EPUB 3. In particular the BG provided critical support to the update of EPUBCheck to validate EPUB content to the new EPUB 3.2 specification. This resulted in the development, in conjunction with the EPUB3 Community Group, of a new generation of EPUBCheck, i.e., EPUBCheck 4.2 production-ready release. Media and Entertainment All Media specifications The Media and Entertainment vertical tracks media-related topics and features that create immersive experiences for end users. HTML5 brought standard audio and video elements to the Web. Standardization activities since then have aimed at turning the Web into a professional platform fully suitable for the delivery of media content and associated materials, enabling missing features to stream video content on the Web such as adaptive streaming and content protection. Together with Microsoft, Comcast, Netflix and Google, W3C received an Technology & Engineering Emmy Award in April 2019 for standardization of a full TV experience on the Web. Current goals are to: Reinforce core media technologies: Creation of the Media Working Group, to develop media-related specifications incubated in the WICG (e.g. Media Capabilities, Picture-in-picture, Media Session) and maintain maintain/evolve Media Source Extensions (MSE) and Encrypted Media Extensions (EME). Improve support for Media Timed Events: data cues incubation. Enhance color support (HDR, wide gamut), in scope of the CSS WG and in the Color on the Web CG. Reduce fragmentation: Continue annual releases of a common and testable baseline media devices, in scope of the Web Media APIs CG and in collaboration with the CTA WAVE Project. Maintain the Road-map of Media Technologies for the Web which highlights Web technologies that can be used to build media applications and services, as well as known gaps to enable additional use cases. Create the future: Discuss perspectives for Media and Entertainment for the Web. Bring the power of GPUs to the Web (graphics, machine learning, heavy processing), under incubation in the GPU for the Web CG. Transition to a Working Group is under discussion. Determine next steps after the successful W3C Workshop on Web Games of June 2019. View the report. Timed Text The Timed Text Working Group develops and maintains formats used for the representation of text synchronized with other timed media, like audio and video, and notably works on TTML, profiles of TTML, and WebVTT. Recent progress includes: A robust WebVTT implementation report poises the specification for publication as a proposed recommendation. Discussions around re-chartering, notably to add a TTML Profile for Audio Description deliverable to the scope of the group, and clarify that rendering of captions within XR content is also in scope. Immersive Web Hardware that enables Virtual Reality (VR) and Augmented Reality (AR) applications are now broadly available to consumers, offering an immersive computing platform with both new opportunities and challenges. The ability to interact directly with immersive hardware is critical to ensuring that the web is well equipped to operate as a first-class citizen in this environment. The Immersive Web Working Group has been stabilizing the WebXR Device API while the companion Immersive Web Community Group incubates the next series of features identified as key for the future of the Immersive Web. W3C plans a workshop focused on the needs and benefits at the intersection of VR & Accessibility (Inclusive XR), on 5-6 November 2019 in Seattle, WA, USA, to explore existing and future approaches on making Virtual and Augmented Reality experiences more inclusive. Web & Telecommunications The Web is the Open Platform for Mobile. Telecommunication service providers and network equipment providers have long been critical actors in the deployment of Web technologies. As the Web platform matures, it brings richer and richer capabilities to extend existing services to new users and devices, and propose new and innovative services. Real-Time Communications (WebRTC) All Real-Time Communications specifications WebRTC has reshaped the whole communication landscape by making any connected device a potential communication end-point, bringing audio and video communications anywhere, on any network, vastly expanding the ability of operators to reach their customers. WebRTC serves as the corner-stone of many online communication and collaboration services. The WebRTC Working Group aims to bringing WebRTC 1.0 (and companion specification Media Capture and Streams) to Recommendation by the end of 2019. Intense efforts are focused on testing (supported by a dedicated hackathon at IETF 104) and interoperability. The group is considering pushing features that have not gotten enough traction to separate modules or to a later minor revision of the spec. Beyond WebRTC 1.0, the WebRTC Working Group will focus its efforts on WebRTC NV which the group has started documenting by identifying use cases. Web & Networks Recently launched, in the wake of the May 2018 Web5G workshop, the Web & Networks Interest Group is chaired by representatives from AT&T, China Mobile and Intel, with a goal to explore solutions for web applications to achieve better performance and resource allocation, both on the device and network. The group's first efforts are around use cases, privacy & security requirements and liaisons. Automotive All Automotive specifications To create a rich application ecosystem for vehicles and other devices allowed to connect to the vehicle, the W3C Automotive Working Group is delivering a service specification to expose all common vehicle signals (engine temperature, fuel/charge level, range, tire pressure, speed, etc.) The Vehicle Information Service Specification (VISS), which is a Candidate Recommendation, is seeing more implementations across the industry. It provides the access method to a common data model for all the vehicle signals –presently encapsulating a thousand or so different data elements– and will be growing to accommodate the advances in automotive such as autonomous and driver assist technologies and electrification. The group is already working on a successor to VISS, leveraging the underlying data model and the VIWI submission from Volkswagen, for a more robust means of accessing vehicle signals information and the same paradigm for other automotive needs including location-based services, media, notifications and caching content. The Automotive and Web Platform Business Group acts as an incubator for prospective standards work. One of its task forces is using W3C VISS in performing data sampling and off-boarding the information to the cloud. Access to the wealth of information that W3C's auto signals standard exposes is of interest to regulators, urban planners, insurance companies, auto manufacturers, fleet managers and owners, service providers and others. In addition to components needed for data sampling and edge computing, capturing user and owner consent, information collection methods and handling of data are in scope. The upcoming W3C Workshop on Data Models for Transportation (September 2019) is expected to focus on the need of additional ontologies around transportation space. Web of Things All Web of Things specifications W3C's Web of Things work is designed to bridge disparate technology stacks to allow devices to work together and achieve scale, thus enabling the potential of the Internet of Things by eliminating fragmentation and fostering interoperability. Thing descriptions expressed in JSON-LD cover the behavior, interaction affordances, data schema, security configuration, and protocol bindings. The Web of Things complements existing IoT ecosystems to reduce the cost and risk for suppliers and consumers of applications that create value by combining multiple devices and information services. There are many sectors that will benefit, e.g. smart homes, smart cities, smart industry, smart agriculture, smart healthcare and many more. The Web of Things Working Group is finishing the initial Web of Things standards, with support from the Web of Things Interest Group: Web of Things Architecture Thing Descriptions Strengthening the Core of the Web HTML The HTML Working Group was chartered early June to assist the W3C community in raising issues and proposing solutions for the HTML and DOM specifications, and to produce W3C Recommendations from WHATWG Review Drafts. A few days before, W3C and the WHATWG signed a Memorandum of Understanding outlining the agreement to collaborate on the development of a single version of the HTML and DOM specifications. Issues and proposed solutions for HTML and DOM done via the newly rechartered HTML Working Group in the WHATWG repositories The HTML Working Group is targetting November 2019 to bring HTML and DOM to Candidate Recommendations. CSS All CSS specifications CSS is a critical part of the Open Web Platform. The CSS Working Group gathers requirements from two large groups of CSS users: the publishing industry and application developers. Within W3C, those groups are exemplified by the Publishing groups and the Web Platform Working Group. The former requires things like better pagination support and advanced font handling, the latter needs intelligent (and fast!) scrolling and animations. What we know as CSS is actually a collection of almost a hundred specifications, referred to as ‘modules’. The current state of CSS is defined by a snapshot, updated once a year. The group also publishes an index defining every term defined by CSS specifications. Fonts All Fonts specifications The Web Fonts Working Group develops specifications that allow the interoperable deployment of downloadable fonts on the Web, with a focus on Progressive Font Enrichment as well as maintenance of WOFF Recommendations. Recent and ongoing work includes: Early API experiments by Adobe and Monotype have demonstrated the feasibility of a font enrichment API, where a server delivers a font with minimal glyph repertoire and the client can query the full repertoire and request additional subsets on-the-fly. In other experiments, the Brotli compression used in WOFF 2 was extended to support shared dictionaries and patch update. Metrics to quantify improvement are a current hot discussion topic. The group will meet at ATypi 2019 in Japan, to gather requirements from the international typography community. The group will first produce a report summarizing the strengths and weaknesses of each prototype solution by Q2 2020. SVG All SVG specifications SVG is an important and widely-used part of the Open Web Platform. The SVG Working Group focuses on aligning the SVG 2.0 specification with browser implementations, having split the specification into a currently-implemented 2.0 and a forward-looking 2.1. Current activity is on stabilization, increased integration with the Open Web Platform, and test coverage analysis. The Working Group was rechartered in March 2019. A new work item concerns native (non-Web-browser) uses of SVG as a non-interactive, vector graphics format. Audio The Web Audio Working Group was extended to finish its work on the Web Audio API, expecting to publish it as a Recommendation by year end. The specification enables synthesizing audio in the browser. Audio operations are performed with audio nodes, which are linked together to form a modular audio routing graph. Multiple sources — with different types of channel layout — are supported. This modular design provides the flexibility to create complex audio functions with dynamic effects. The first version of Web Audio API is now feature complete and is implemented in all modern browsers. Work has started on the next version, and new features are being incubated in the Audio Community Group. Performance Web Performance All Web Performance specifications There are currently 18 specifications in development in the Web Performance Working Group aiming to provide methods to observe and improve aspects of application performance of user agent features and APIs. The W3C team is looking at related work incubated in the W3C GPU for the Web (WebGPU) Community Group which is poised to transition to a W3C Working Group. A preliminary draft charter is available. WebAssembly All WebAssembly specifications WebAssembly improves Web performance and power by being a virtual machine and execution environment enabling loaded pages to run native (compiled) code. It is deployed in Firefox, Edge, Safari and Chrome. The specification will soon reach Candidate Recommendation. WebAssembly enables near-native performance, optimized load time, and perhaps most importantly, a compilation target for existing code bases. While it has a small number of native types, much of the performance increase relative to Javascript derives from its use of consistent typing. WebAssembly leverages decades of optimization for compiled languages and the byte code is optimized for compactness and streaming (the web page starts executing while the rest of the code downloads). Network and API access all occurs through accompanying Javascript libraries -- the security model is identical to that of Javascript. Requirements gathering and language development occur in the Community Group while the Working Group manages test development, community review and progression of specifications on the Recommendation Track. Testing Browser testing plays a critical role in the growth of the Web by: Improving the reliability of Web technology definitions; Improving the quality of implementations of these technologies by helping vendors to detect bugs in their products; Improving the data available to Web developers on known bugs and deficiencies of Web technologies by publishing results of these tests. Browser Testing and Tools The Browser Testing and Tools Working Group is developing WebDriver version 2, having published last year the W3C Recommendation of WebDriver. WebDriver acts as a remote control interface that enables introspection and control of user agents, provides a platform- and language-neutral wire protocol as a way for out-of-process programs to remotely instruct the behavior of Web, and emulates the actions of a real person using the browser. WebPlatform Tests The WebPlatform Tests project now provides a mechanism which allows to fully automate tests that previously needed to be run manually: TestDriver. TestDriver enables sending trusted key and mouse events, sending complex series of trusted pointer and key interactions for things like in-content drag-and-drop or pinch zoom, and even file upload. Since 2014 W3C began work on this coordinated open-source effort to build a cross-browser test suite for the Web Platform, which WHATWG, and all major browsers adopted. Web of Data All Data specifications There have been several great success stories around the standardization of data on the web over the past year. Verifiable Claims seems to have significant uptake. It is also significant that the Distributed Identifier WG charter has received numerous favorable reviews, and was just recently launched. JSON-LD has been a major success with the large deployment on Web sites via schema.org. JSON-LD 1.1 completed technical work, about to transition to CR More than 25% of websites today include schema.org data in JSON-LD The Web of Things description is in CR since May, making use of JSON-LD Verifiable Credentials data model is in CR since July, also making use of JSON-LD Continued strong interest in decentralized identifiers Engagement from the TAG with reframing core documents, such as Ethical Web Principles, to include data on the web within their scope Data is increasingly important for all organizations, especially with the rise of IoT and Big Data. W3C has a mature and extensive suite of standards relating to data that were developed over two decades of experience, with plans for further work on making it easier for developers to work with graph data and knowledge graphs. Linked Data is about the use of URIs as names for things, the ability to dereference these URIs to get further information and to include links to other data. There are ever-increasing sources of open Linked Data on the Web, as well as data services that are restricted to the suppliers and consumers of those services. The digital transformation of industry is seeking to exploit advanced digital technologies. This will facilitate businesses to integrate horizontally along the supply and value chains, and vertically from the factory floor to the office floor. W3C is seeking to make it easier to support enterprise-wide data management and governance, reflecting the strategic importance of data to modern businesses. Traditional approaches to data have focused on tabular databases (SQL/RDBMS), Comma Separated Value (CSV) files, and data embedded in PDF documents and spreadsheets. We're now in midst of a major shift to graph data with nodes and labeled directed links between them. Graph data is: Faster than using SQL and associated JOIN operations More favorable to integrating data from heterogeneous sources Better suited to situations where the data model is evolving In the wake of the recent W3C Workshop on Graph Data we are in the process of launching a Graph Standardization Business Group to provide a business perspective with use cases and requirements, to coordinate technical standards work and liaisons with external organizations. Web for All Security, Privacy, Identity All Security specifications, all Privacy specifications Authentication on the Web As the WebAuthn Level 1 W3C Recommendation published last March is seeing wide implementation and adoption of strong cryptographic authentication, work is proceeding on Level 2. The open standard Web API gives native authentication technology built into native platforms, browsers, operating systems (including mobile) and hardware, offering protection against hacking, credential theft, phishing attacks, thus aiming to end the era of passwords as a security construct. You may read more in our March press release. Privacy An increasing number of W3C specifications are benefitting from Privacy and Security review; there are security and privacy aspects to every specification. Early review is essential. Working with the TAG, the Privacy Interest Group has updated the Self-Review Questionnaire: Security and Privacy. Other recent work of the group includes public blogging further to the exploration of anti-patterns in standards and permission prompts. Security The Web Application Security Working Group adopted Feature Policy, aiming to allow developers to selectively enable, disable, or modify the behavior of some of these browser features and APIs within their application; and Fetch Metadata, aiming to provide servers with enough information to make a priori decisions about whether or not to service a request based on the way it was made, and the context in which it will be used. The Web Payment Security Interest Group, launched last April, convenes members from W3C, EMVCo, and the FIDO Alliance to discuss cooperative work to enhance the security and interoperability of Web payments (read more about payments). Internationalization (i18n) All Internationalization specifications, educational articles related to Internationalization, spec developers checklist Only a quarter or so current Web users use English online and that proportion will continue to decrease as the Web reaches more and more communities of limited English proficiency. If the Web is to live up to the "World Wide" portion of its name, and for the Web to truly work for stakeholders all around the world engaging with content in various languages, it must support the needs of worldwide users as they engage with content in the various languages. The growth of epublishing also brings requirements for new features and improved typography on the Web. It is important to ensure the needs of local communities are captured. The W3C Internationalization Initiative was set up to increase in-house resources dedicated to accelerating progress in making the World Wide Web "worldwide" by gathering user requirements, supporting developers, and education & outreach. For an overview of current projects see the i18n radar. W3C's Internationalization efforts progressed on a number of fronts recently: Requirements: New African and European language groups will work on the gap analysis, errata and layout requirements. Gap analysis: Japanese, Devanagari, Bengali, Tamil, Lao, Khmer, Javanese, and Ethiopic updated in the gap-analysis documents. Layout requirements document: notable progress tracked in the Southeast Asian Task Force while work continues on Chinese layout requirements. Developer support: Spec reviews: the i18n WG continues active review of specifications of the WHATWG and other W3C Working Groups. Short review checklist: easy way to begin a self-review to help spec developers understand what aspects of their spec are likely to need attention for internationalization, and points them to more detailed checklists for the relevant topics. It also helps those reviewing specs for i18n issues. Strings on the Web: Language and Direction Metadata lays out issues and discusses potential solutions for passing information about language and direction with strings in JSON or other data formats. The document was rewritten for clarity, and expanded. The group is collaborating with the JSON-LD and Web Publishing groups to develop a plan for updating RDF, JSON-LD and related specifications to handle metadata for base direction of text (bidi). User-friendly test format: a new format was developed for Internationalization Test Suite tests, which displays helpful information about how the test works. This particularly useful because those tests are pointed to by educational materials and gap-analysis documents. Web Platform Tests: a large number of tests in the i18n test suite have been ported to the WPT repository, including: css-counter-styles, css-ruby, css-syntax, css-test, css-text-decor, css-writing-modes, and css-pseudo. Education & outreach: (for all educational materials, see the HTML & CSS Authoring Techniques) Web Accessibility All Accessibility specifications, WAI resources The Web Accessibility Initiative supports W3C's Web for All mission. Recent achievements include: Education and training: Inaccessibility of CAPTCHA updated to bring our analysis and recommendations up to date with CAPTCHA practice today, concluding two years of extensive work and invaluable input from the public (read more on the W3C Blog Learn why your web content and applications should be accessible. The Education and Outreach Working Group has completed revision and updating of the Business Case for Digital Accessibility. Accessibility guidelines: The Accessibility Guidelines Working Group has continued to update WCAG Techniques and Understanding WCAG 2.1; and published a Candidate Recommendation of Accessibility Conformance Testing Rules Format 1.0 to improve inter-rater reliability when evaluating conformance of web content to WCAG An updated charter is being developed to host work on "Silver", the next generation accessibility guidelines (WCAG 2.2) There are accessibility aspects to most specifications. Check your work with the FAST checklist. Outreach to the world W3C Developer Relations To foster the excellent feedback loop between Web Standards development and Web developers, and to grow participation from that diverse community, recent W3C Developer Relations activities include: @w3cdevs tracks the enormous amount of work happening across W3C W3C Track during the Web Conference 2019 in San Francisco Tech videos: W3C published the 2019 Web Games Workshop videos The 16 September 2019 Developer Meetup in Fukuoka, Japan, is open to all and will combine a set of technical demos prepared by W3C groups, and a series of talks on a selected set of W3C technologies and projects W3C is involved with Mozilla, Google, Samsung, Microsoft and Bocoup in the organization of ViewSource 2019 in Amsterdam (read more on the W3C Blog) W3C Training In partnership with EdX, W3C's MOOC training program, W3Cx offers a complete "Front-End Web Developer" (FEWD) professional certificate program that consists of a suite of five courses on the foundational languages that power the Web: HTML5, CSS and JavaScript. We count nearly 900K students from all over the world. Translations Many Web users rely on translations of documents developed at W3C whose official language is English. W3C is extremely grateful to the continuous efforts of its community in ensuring our various deliverables in general, and in our specifications in particular, are made available in other languages, for free, ensuring their exposure to a much more diverse set of readers. Last Spring we developed a more robust system, a new listing of translations of W3C specifications and updated the instructions on how to contribute to our translation efforts. W3C Liaisons Liaisons and coordination with numerous organizations and Standards Development Organizations (SDOs) is crucial for W3C to: make sure standards are interoperable coordinate our respective agenda in Internet governance: W3C participates in ICANN, GIPO, IGF, the I* organizations (ICANN, IETF, ISOC, IAB). ensure at the government liaison level that our standards work is officially recognized when important to our membership so that products based on them (often done by our members) are part of procurement orders. W3C has ARO/PAS status with ISO. W3C participates in the EU MSP and Rolling Plan on Standardization ensure the global set of Web and Internet standards form a compatible stack of technologies, at the technical and policy level (patent regime, fragmentation, use in policy making) promote Standards adoption equally by the industry, the public sector, and the public at large Coralie Mercier, Editor, W3C Marketing & Communications $Id: Overview.html,v 1.60 2019/10/15 12:05:52 coralie Exp $ Copyright © 2019 W3C ® (MIT, ERCIM, Keio, Beihang) Usage policies apply.

Conversion of PDF documents to structured Markdown, optimized for Retrieval Augmented Generation (RAG) and other NLP tasks. Extract text, tables, and images with preserved formatting for enhanced information retrieval and processing.

🤖 HealthCare ChatBot Major -1 (4th year - 7th semester) Health Care Chat-Bot is a Healthcare Domain Chatbot to simulate the predictions of a General Physician. ChatBot can be described as software that can chat with people using artificial intelligence. These software are used to perform tasks such as quickly responding to users, informing them, helping to purchase products and providing better service to customers. We have made a healthcare based chatbot. The three main areas where chatbots can be used are diagnostics, patient engagement outside medical facilities, and mental health. In our major we are working on diagnostic. 📃 Brief A chatbot is an artificially intelligent creature which can converse with humans. This could be text-based, or a spoken conversation. In our project we will be using Python as it is currently the most popular language for creating an AI chatbot. In the middle of AI chatbot, architecture is the Natural Language Processing (NLP) layer. This project aims to build an user-friendly healthcare chatbot which facilitates the job of a healthcare provider and helps improve their performance by interacting with users in a human-like way. Through chatbots one can communicate with text or voice interface and get reply through artificial intelligence Typically, a chat bot will communicate with a real person. Chat bots are used in applications such as E-commerce customer service, Call centres, Internet gaming,etc. Chatbots are programs built to automatically engage with received messages. Chatbots can be programmed to respond the same way each time, to respond differently to messages containing certain keywords and even to use machine learning to adapt their responses to fit the situation. A developing number of hospitals, nursing homes, and even private centres, presently utilize online Chatbots for human services on their sites. These bots connect with potential patients visiting the site, helping them discover specialists, booking their appointments, and getting them access to the correct treatment. In any case, the utilization of artificial intelligence in an industry where individuals’ lives could be in question, still starts misgivings in individuals. It brings up issues about whether the task mentioned above ought to be assigned to human staff. This healthcare chatbot system will help hospitals to provide healthcare support online 24 x 7, it answers deep as well as general questions. It also helps to generate leads and automatically delivers the information of leads to sales. By asking the questions in series it helps patients by guiding what exactly he/she is looking for. 📜 Problem Statement During the pandemic, it is more important than ever to get your regular check-ups and to continue to take prescription medications. The healthier you are, the more likely you are to recover quickly from an illness. In this time patients or health care workers within their practice, providers are deferring elective and preventive visits, such as annual physicals. For some, it is not possible to consult online. In this case, to avoid false information, our project can be of help. 📇 Features Register Screen. Sign-in Screen. Generates database for user login system. Offers you a GUI Based Chatbot for patients for diagnosing. [A pragmatic Approach for Diagnosis] Reccomends an appropriate doctor to you for the following symptom. 📜 Modules Used Our program uses a number of python modules to work properly: tkinter os webbrowser numpy pandas matplotlib 📃 Algorithm We have used Decision tree for our health care based chat bot. Decision Tree is a Supervised learning technique that can be used for both classification and Regression problems, but mostly it is preferred for solving Classification problems. It is a tree-structured classifier, where internal nodes represent the features of a dataset, branches represent the decision rules and each leaf node represents the outcome.It usually mimic human thinking ability while making a decision, so it is easy to understand. :suspect: Project Members Anushka Bansal - 500067844 - R164218014 Shreya Sharma - 500068573 - R164218070 Silvi - 500069092 - R164218072 Ishika Agrawal - 500071154 - R164218097

Pybot can change the way learners try to learn python programming language in a more interactive way. This chatbot will try to solve or provide answer to almost every python related issues or queries that the user is asking for. We are implementing NLP for improving the efficiency of the chatbot. We will include voice feature for more interactivity to the user. By utilizing NLP, developers can organize and structure knowledge to perform tasks such as automatic summarization, translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, and topic segmentation. NLTK has been called “a wonderful tool for teaching and working in, computational linguistics using Python,” and “an amazing library to play with natural language.The main issue with text data is that it is all in text format (strings). However, the Machine learning algorithms need some sort of numerical feature vector in order to perform the task. So before we start with any NLP project we need to pre-process it to make it ideal for working. Converting the entire text into uppercase or lowercase, so that the algorithm does not treat the same words in different cases as different Tokenization is just the term used to describe the process of converting the normal text strings into a list of tokens i.e words that we actually want. Sentence tokenizer can be used to find the list of sentences and Word tokenizer can be used to find the list of words in strings.Removing Noise i.e everything that isn’t in a standard number or letter.Removing Stop words. Sometimes, some extremely common words which would appear to be of little value in helping select documents matching a user need are excluded from the vocabulary entirely. These words are called stop words.Stemming is the process of reducing inflected (or sometimes derived) words to their stem, base or root form — generally a written word form. Example if we were to stem the following words: “Stems”, “Stemming”, “Stemmed”, “and Stemtization”, the result would be a single word “stem”. A slight variant of stemming is lemmatization. The major difference between these is, that, stemming can often create non-existent words, whereas lemmas are actual words. So, your root stem, meaning the word you end up with, is not something you can just look up in a dictionary, but you can look up a lemma. Examples of Lemmatization are that “run” is a base form for words like “running” or “ran” or that the word “better” and “good” are in the same lemma so they are considered the same.

An ANN is a model based on a collection of connected units or nodes called "artificial neurons", which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit information, a "signal", from one artificial neuron to another. An artificial neuron that receives a signal can process it and then signal additional artificial neurons connected to it. In common ANN implementations, the signal at a connection between artificial neurons is a real number, and the output of each artificial neuron is computed by some non-linear function of the sum of its inputs. The connections between artificial neurons are called "edges". Artificial neurons and edges typically have a weight that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection. Artificial neurons may have a threshold such that the signal is only sent if the aggregate signal crosses that threshold. Typically, artificial neurons are aggregated into layers. Different layers may perform different kinds of transformations on their inputs. Signals travel from the first layer (the input layer) to the last layer (the output layer), possibly after traversing the layers multiple times. The original goal of the ANN approach was to solve problems in the same way that a human brain would. However, over time, attention moved to performing specific tasks, leading to deviations from biology. Artificial neural networks have been used on a variety of tasks, including computer vision, speech recognition, machine translation, social network filtering, playing board and video games and medical diagnosis. Deep learning consists of multiple hidden layers in an artificial neural network. This approach tries to model the way the human brain processes light and sound into vision and hearing. Some successful applications of deep learning are computer vision and speech recognition.[68] Decision trees Main article: Decision tree learning Decision tree learning uses a decision tree as a predictive model to go from observations about an item (represented in the branches) to conclusions about the item's target value (represented in the leaves). It is one of the predictive modeling approaches used in statistics, data mining, and machine learning. Tree models where the target variable can take a discrete set of values are called classification trees; in these tree structures, leaves represent class labels and branches represent conjunctions of features that lead to those class labels. Decision trees where the target variable can take continuous values (typically real numbers) are called regression trees. In decision analysis, a decision tree can be used to visually and explicitly represent decisions and decision making. In data mining, a decision tree describes data, but the resulting classification tree can be an input for decision making. Support vector machines Main article: Support vector machines Support vector machines (SVMs), also known as support vector networks, are a set of related supervised learning methods used for classification and regression. Given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that predicts whether a new example falls into one category or the other.[69] An SVM training algorithm is a non-probabilistic, binary, linear classifier, although methods such as Platt scaling exist to use SVM in a probabilistic classification setting. In addition to performing linear classification, SVMs can efficiently perform a non-linear classification using what is called the kernel trick, implicitly mapping their inputs into high-dimensional feature spaces. Illustration of linear regression on a data set. Regression analysis Main article: Regression analysis Regression analysis encompasses a large variety of statistical methods to estimate the relationship between input variables and their associated features. Its most common form is linear regression, where a single line is drawn to best fit the given data according to a mathematical criterion such as ordinary least squares. The latter is often extended by regularization (mathematics) methods to mitigate overfitting and bias, as in ridge regression. When dealing with non-linear problems, go-to models include polynomial regression (for example, used for trendline fitting in Microsoft Excel[70]), logistic regression (often used in statistical classification) or even kernel regression, which introduces non-linearity by taking advantage of the kernel trick to implicitly map input variables to higher-dimensional space. Bayesian networks Main article: Bayesian network A simple Bayesian network. Rain influences whether the sprinkler is activated, and both rain and the sprinkler influence whether the grass is wet. A Bayesian network, belief network, or directed acyclic graphical model is a probabilistic graphical model that represents a set of random variables and their conditional independence with a directed acyclic graph (DAG). For example, a Bayesian network could represent the probabilistic relationships between diseases and symptoms. Given symptoms, the network can be used to compute the probabilities of the presence of various diseases. Efficient algorithms exist that perform inference and learning. Bayesian networks that model sequences of variables, like speech signals or protein sequences, are called dynamic Bayesian networks. Generalizations of Bayesian networks that can represent and solve decision problems under uncertainty are called influence diagrams. Genetic algorithms Main article: Genetic algorithm A genetic algorithm (GA) is a search algorithm and heuristic technique that mimics the process of natural selection, using methods such as mutation and crossover to generate new genotypes in the hope of finding good solutions to a given problem. In machine learning, genetic algorithms were used in the 1980s and 1990s.[71][72] Conversely, machine learning techniques have been used to improve the performance of genetic and evolutionary algorithms.[73] Training models Usually, machine learning models require a lot of data in order for them to perform well. Usually, when training a machine learning model, one needs to collect a large, representative sample of data from a training set. Data from the training set can be as varied as a corpus of text, a collection of images, and data collected from individual users of a service. Overfitting is something to watch out for when training a machine learning model. Federated learning Main article: Federated learning Federated learning is an adapted form of distributed artificial intelligence to training machine learning models that decentralizes the training process, allowing for users' privacy to be maintained by not needing to send their data to a centralized server. This also increases efficiency by decentralizing the training process to many devices. For example, Gboard uses federated machine learning to train search query prediction models on users' mobile phones without having to send individual searches back to Google.[74] Applications There are many applications for machine learning, including: Agriculture Anatomy Adaptive websites Affective computing Banking Bioinformatics Brain–machine interfaces Cheminformatics Citizen science Computer networks Computer vision Credit-card fraud detection Data quality DNA sequence classification Economics Financial market analysis[75] General game playing Handwriting recognition Information retrieval Insurance Internet fraud detection Linguistics Machine learning control Machine perception Machine translation Marketing Medical diagnosis Natural language processing Natural language understanding Online advertising Optimization Recommender systems Robot locomotion Search engines Sentiment analysis Sequence mining Software engineering Speech recognition Structural health monitoring Syntactic pattern recognition Telecommunication Theorem proving Time series forecasting User behavior analytics In 2006, the media-services provider Netflix held the first "Netflix Prize" competition to find a program to better predict user preferences and improve the accuracy of its existing Cinematch movie recommendation algorithm by at least 10%. A joint team made up of researchers from AT&T Labs-Research in collaboration with the teams Big Chaos and Pragmatic Theory built an ensemble model to win the Grand Prize in 2009 for $1 million.[76] Shortly after the prize was awarded, Netflix realized that viewers' ratings were not the best indicators of their viewing patterns ("everything is a recommendation") and they changed their recommendation engine accordingly.[77] In 2010 The Wall Street Journal wrote about the firm Rebellion Research and their use of machine learning to predict the financial crisis.[78] In 2012, co-founder of Sun Microsystems, Vinod Khosla, predicted that 80% of medical doctors' jobs would be lost in the next two decades to automated machine learning medical diagnostic software.[79] In 2014, it was reported that a machine learning algorithm had been applied in the field of art history to study fine art paintings and that it may have revealed previously unrecognized influences among artists.[80] In 2019 Springer Nature published the first research book created using machine learning.[81] Limitations Although machine learning has been transformative in some fields, machine-learning programs often fail to deliver expected results.[82][83][84] Reasons for this are numerous: lack of (suitable) data, lack of access to the data, data bias, privacy problems, badly chosen tasks and algorithms, wrong tools and people, lack of resources, and evaluation problems.[85] In 2018, a self-driving car from Uber failed to detect a pedestrian, who was killed after a collision.[86] Attempts to use machine learning in healthcare with the IBM Watson system failed to deliver even after years of time and billions of dollars invested.[87][88] Bias Main article: Algorithmic bias Machine learning approaches in particular can suffer from different data biases. A machine learning system trained on current customers only may not be able to predict the needs of new customer groups that are not represented in the training data. When trained on man-made data, machine learning is likely to pick up the same constitutional and unconscious biases already present in society.[89] Language models learned from data have been shown to contain human-like biases.[90][91] Machine learning systems used for criminal risk assessment have been found to be biased against black people.[92][93] In 2015, Google photos would often tag black people as gorillas,[94] and in 2018 this still was not well resolved, but Google reportedly was still using the workaround to remove all gorillas from the training data, and thus was not able to recognize real gorillas at all.[95] Similar issues with recognizing non-white people have been found in many other systems.[96] In 2016, Microsoft tested a chatbot that learned from Twitter, and it quickly picked up racist and sexist language.[97] Because of such challenges, the effective use of machine learning may take longer to be adopted in other domains.[98] Concern for fairness in machine learning, that is, reducing bias in machine learning and propelling its use for human good is increasingly expressed by artificial intelligence scientists, including Fei-Fei Li, who reminds engineers that "There’s nothing artificial about AI...It’s inspired by people, it’s created by people, and—most importantly—it impacts people. It is a powerful tool we are only just beginning to understand, and that is a profound responsibility.”[99] Model assessments Classification of machine learning models can be validated by accuracy estimation techniques like the holdout method, which splits the data in a training and test set (conventionally 2/3 training set and 1/3 test set designation) and evaluates the performance of the training model on the test set. In comparison, the K-fold-cross-validation method randomly partitions the data into K subsets and then K experiments are performed each respectively considering 1 subset for evaluation and the remaining K-1 subsets for training the model. In addition to the holdout and cross-validation methods, bootstrap, which samples n instances with replacement from the dataset, can be used to assess model accuracy.[100] In addition to overall accuracy, investigators frequently report sensitivity and specificity meaning True Positive Rate (TPR) and True Negative Rate (TNR) respectively. Similarly, investigators sometimes report the false positive rate (FPR) as well as the false negative rate (FNR). However, these rates are ratios that fail to reveal their numerators and denominators. The total operating characteristic (TOC) is an effective method to express a model's diagnostic ability. TOC shows the numerators and denominators of the previously mentioned rates, thus TOC provides more information than the commonly used receiver operating characteristic (ROC) and ROC's associated area under the curve (AUC).[101] Ethics Machine learning poses a host of ethical questions. Systems which are trained on datasets collected with biases may exhibit these biases upon use (algorithmic bias), thus digitizing cultural prejudices.[102] For example, using job hiring data from a firm with racist hiring policies may lead to a machine learning system duplicating the bias by scoring job applicants against similarity to previous successful applicants.[103][104] Responsible collection of data and documentation of algorithmic rules used by a system thus is a critical part of machine learning. Because human languages contain biases, machines trained on language corpora will necessarily also learn these biases.[105][106] Other forms of ethical challenges, not related to personal biases, are more seen in health care. There are concerns among health care professionals that these systems might not be designed in the public's interest but as income-generating machines. This is especially true in the United States where there is a long-standing ethical dilemma of improving health care, but also increasing profits. For example, the algorithms could be designed to provide patients with unnecessary tests or medication in which the algorithm's proprietary owners hold stakes. There is huge potential for machine learning in health care to provide professionals a great tool to diagnose, medicate, and even plan recovery paths for patients, but this will not happen until the personal biases mentioned previously, and these "greed" biases are addressed.[107] Hardware Since the 2010s, advances in both machine learning algorithms and computer hardware have led to more efficient methods for training deep neural networks (a particular narrow subdomain of machine learning) that contain many layers of non-linear hidden units.[108] By 2019, graphic processing units (GPUs), often with AI-specific enhancements, had displaced CPUs as the dominant method of training large-scale commercial cloud AI.[109] OpenAI estimated the hardware compute used in the largest deep learning projects from AlexNet (2012) to AlphaZero (2017), and found a 300,000-fold increase in the amount of compute required, with a doubling-time trendline of 3.4 months.[110][111] Software Software suites containing a variety of machine learning algorithms include the following: Free and open-source so

# big-o-performance A simple html app to demonstrate performance costs of data structures. - Clone the project - Navigate to the root of the project in a termina or command prompt - Run 'npm install' - Run 'npm start' - Go to the URL specified in the terminal or command prompt to try out the app. # This app was created from the Create React App NPM. Below are instructions from that project. Below you will find some information on how to perform common tasks. You can find the most recent version of this guide [here](https://github.com/facebookincubator/create-react-app/blob/master/template/README.md). ## Table of Contents - [Updating to New Releases](#updating-to-new-releases) - [Sending Feedback](#sending-feedback) - [Folder Structure](#folder-structure) - [Available Scripts](#available-scripts) - [npm start](#npm-start) - [npm run build](#npm-run-build) - [npm run eject](#npm-run-eject) - [Displaying Lint Output in the Editor](#displaying-lint-output-in-the-editor) - [Installing a Dependency](#installing-a-dependency) - [Importing a Component](#importing-a-component) - [Adding a Stylesheet](#adding-a-stylesheet) - [Post-Processing CSS](#post-processing-css) - [Adding Images and Fonts](#adding-images-and-fonts) - [Adding Bootstrap](#adding-bootstrap) - [Adding Flow](#adding-flow) - [Adding Custom Environment Variables](#adding-custom-environment-variables) - [Integrating with a Node Backend](#integrating-with-a-node-backend) - [Proxying API Requests in Development](#proxying-api-requests-in-development) - [Deployment](#deployment) - [Now](#now) - [Heroku](#heroku) - [Surge](#surge) - [GitHub Pages](#github-pages) - [Something Missing?](#something-missing) ## Updating to New Releases Create React App is divided into two packages: * `create-react-app` is a global command-line utility that you use to create new projects. * `react-scripts` is a development dependency in the generated projects (including this one). You almost never need to update `create-react-app` itself: it’s delegates all the setup to `react-scripts`. When you run `create-react-app`, it always creates the project with the latest version of `react-scripts` so you’ll get all the new features and improvements in newly created apps automatically. To update an existing project to a new version of `react-scripts`, [open the changelog](https://github.com/facebookincubator/create-react-app/blob/master/CHANGELOG.md), find the version you’re currently on (check `package.json` in this folder if you’re not sure), and apply the migration instructions for the newer versions. In most cases bumping the `react-scripts` version in `package.json` and running `npm install` in this folder should be enough, but it’s good to consult the [changelog](https://github.com/facebookincubator/create-react-app/blob/master/CHANGELOG.md) for potential breaking changes. We commit to keeping the breaking changes minimal so you can upgrade `react-scripts` painlessly. ## Sending Feedback We are always open to [your feedback](https://github.com/facebookincubator/create-react-app/issues). ## Folder Structure After creation, your project should look like this: ``` my-app/ README.md index.html favicon.ico node_modules/ package.json src/ App.css App.js index.css index.js logo.svg ``` For the project to build, **these files must exist with exact filenames**: * `index.html` is the page template; * `favicon.ico` is the icon you see in the browser tab; * `src/index.js` is the JavaScript entry point. You can delete or rename the other files. You may create subdirectories inside `src`. For faster rebuilds, only files inside `src` are processed by Webpack. You need to **put any JS and CSS files inside `src`**, or Webpack won’t see them. You can, however, create more top-level directories. They will not be included in the production build so you can use them for things like documentation. ## Available Scripts In the project directory, you can run: ### `npm start` Runs the app in the development mode.<br> Open [http://localhost:3000](http://localhost:3000) to view it in the browser. The page will reload if you make edits.<br> You will also see any lint errors in the console. ### `npm run build` Builds the app for production to the `build` folder.<br> It correctly bundles React in production mode and optimizes the build for the best performance. The build is minified and the filenames include the hashes.<br> Your app is ready to be deployed! ### `npm run eject` **Note: this is a one-way operation. Once you `eject`, you can’t go back!** If you aren’t satisfied with the build tool and configuration choices, you can `eject` at any time. This command will remove the single build dependency from your project. Instead, it will copy all the configuration files and the transitive dependencies (Webpack, Babel, ESLint, etc) right into your project so you have full control over them. All of the commands except `eject` will still work, but they will point to the copied scripts so you can tweak them. At this point you’re on your own. You don’t have to ever use `eject`. The curated feature set is suitable for small and middle deployments, and you shouldn’t feel obligated to use this feature. However we understand that this tool wouldn’t be useful if you couldn’t customize it when you are ready for it. ## Displaying Lint Output in the Editor >Note: this feature is available with `react-scripts@0.2.0` and higher. Some editors, including Sublime Text, Atom, and Visual Studio Code, provide plugins for ESLint. They are not required for linting. You should see the linter output right in your terminal as well as the browser console. However, if you prefer the lint results to appear right in your editor, there are some extra steps you can do. You would need to install an ESLint plugin for your editor first. >**A note for Atom `linter-eslint` users** >If you are using the Atom `linter-eslint` plugin, make sure that **Use global ESLint installation** option is checked: ><img src="http://i.imgur.com/yVNNHJM.png" width="300"> Then make sure `package.json` of your project ends with this block: ```js { // ... "eslintConfig": { "extends": "./node_modules/react-scripts/config/eslint.js" } } ``` Projects generated with `react-scripts@0.2.0` and higher should already have it. If you don’t need ESLint integration with your editor, you can safely delete those three lines from your `package.json`. Finally, you will need to install some packages *globally*: ```sh npm install -g eslint babel-eslint eslint-plugin-react eslint-plugin-import eslint-plugin-jsx-a11y eslint-plugin-flowtype ``` We recognize that this is suboptimal, but it is currently required due to the way we hide the ESLint dependency. The ESLint team is already [working on a solution to this](https://github.com/eslint/eslint/issues/3458) so this may become unnecessary in a couple of months. ## Installing a Dependency The generated project includes React and ReactDOM as dependencies. It also includes a set of scripts used by Create React App as a development dependency. You may install other dependencies (for example, React Router) with `npm`: ``` npm install --save <library-name> ``` ## Importing a Component This project setup supports ES6 modules thanks to Babel. While you can still use `require()` and `module.exports`, we encourage you to use [`import` and `export`](http://exploringjs.com/es6/ch_modules.html) instead. For example: ### `Button.js` ```js import React, { Component } from 'react'; class Button extends Component { render() { // ... } } export default Button; // Don’t forget to use export default! ``` ### `DangerButton.js` ```js import React, { Component } from 'react'; import Button from './Button'; // Import a component from another file class DangerButton extends Component { render() { return <Button color="red" />; } } export default DangerButton; ``` Be aware of the [difference between default and named exports](http://stackoverflow.com/questions/36795819/react-native-es-6-when-should-i-use-curly-braces-for-import/36796281#36796281). It is a common source of mistakes. We suggest that you stick to using default imports and exports when a module only exports a single thing (for example, a component). That’s what you get when you use `export default Button` and `import Button from './Button'`. Named exports are useful for utility modules that export several functions. A module may have at most one default export and as many named exports as you like. Learn more about ES6 modules: * [When to use the curly braces?](http://stackoverflow.com/questions/36795819/react-native-es-6-when-should-i-use-curly-braces-for-import/36796281#36796281) * [Exploring ES6: Modules](http://exploringjs.com/es6/ch_modules.html) * [Understanding ES6: Modules](https://leanpub.com/understandinges6/read#leanpub-auto-encapsulating-code-with-modules) ## Adding a Stylesheet This project setup uses [Webpack](https://webpack.github.io/) for handling all assets. Webpack offers a custom way of “extending” the concept of `import` beyond JavaScript. To express that a JavaScript file depends on a CSS file, you need to **import the CSS from the JavaScript file**: ### `Button.css` ```css .Button { padding: 20px; } ``` ### `Button.js` ```js import React, { Component } from 'react'; import './Button.css'; // Tell Webpack that Button.js uses these styles class Button extends Component { render() { // You can use them as regular CSS styles return <div className="Button" />; } } ``` **This is not required for React** but many people find this feature convenient. You can read about the benefits of this approach [here](https://medium.com/seek-ui-engineering/block-element-modifying-your-javascript-components-d7f99fcab52b). However you should be aware that this makes your code less portable to other build tools and environments than Webpack. In development, expressing dependencies this way allows your styles to be reloaded on the fly as you edit them. In production, all CSS files will be concatenated into a single minified `.css` file in the build output. If you are concerned about using Webpack-specific semantics, you can put all your CSS right into `src/index.css`. It would still be imported from `src/index.js`, but you could always remove that import if you later migrate to a different build tool. ## Post-Processing CSS This project setup minifies your CSS and adds vendor prefixes to it automatically through [Autoprefixer](https://github.com/postcss/autoprefixer) so you don’t need to worry about it. For example, this: ```css .App { display: flex; flex-direction: row; align-items: center; } ``` becomes this: ```css .App { display: -webkit-box; display: -ms-flexbox; display: flex; -webkit-box-orient: horizontal; -webkit-box-direction: normal; -ms-flex-direction: row; flex-direction: row; -webkit-box-align: center; -ms-flex-align: center; align-items: center; } ``` There is currently no support for preprocessors such as Less, or for sharing variables across CSS files. ## Adding Images and Fonts With Webpack, using static assets like images and fonts works similarly to CSS. You can **`import` an image right in a JavaScript module**. This tells Webpack to include that image in the bundle. Unlike CSS imports, importing an image or a font gives you a string value. This value is the final image path you can reference in your code. Here is an example: ```js import React from 'react'; import logo from './logo.png'; // Tell Webpack this JS file uses this image console.log(logo); // /logo.84287d09.png function Header() { // Import result is the URL of your image return <img src={logo} alt="Logo" />; } export default function Header; ``` This works in CSS too: ```css .Logo { background-image: url(./logo.png); } ``` Webpack finds all relative module references in CSS (they start with `./`) and replaces them with the final paths from the compiled bundle. If you make a typo or accidentally delete an important file, you will see a compilation error, just like when you import a non-existent JavaScript module. The final filenames in the compiled bundle are generated by Webpack from content hashes. If the file content changes in the future, Webpack will give it a different name in production so you don’t need to worry about long-term caching of assets. Please be advised that this is also a custom feature of Webpack. **It is not required for React** but many people enjoy it (and React Native uses a similar mechanism for images). However it may not be portable to some other environments, such as Node.js and Browserify. If you prefer to reference static assets in a more traditional way outside the module system, please let us know [in this issue](https://github.com/facebookincubator/create-react-app/issues/28), and we will consider support for this. ## Adding Bootstrap You don’t have to use [React Bootstrap](https://react-bootstrap.github.io) together with React but it is a popular library for integrating Bootstrap with React apps. If you need it, you can integrate it with Create React App by following these steps: Install React Bootstrap and Bootstrap from NPM. React Bootstrap does not include Bootstrap CSS so this needs to be installed as well: ``` npm install react-bootstrap --save npm install bootstrap@3 --save ``` Import Bootstrap CSS and optionally Bootstrap theme CSS in the ```src/index.js``` file: ```js import 'bootstrap/dist/css/bootstrap.css'; import 'bootstrap/dist/css/bootstrap-theme.css'; ``` Import required React Bootstrap components within ```src/App.js``` file or your custom component files: ```js import { Navbar, Jumbotron, Button } from 'react-bootstrap'; ``` Now you are ready to use the imported React Bootstrap components within your component hierarchy defined in the render method. Here is an example [`App.js`](https://gist.githubusercontent.com/gaearon/85d8c067f6af1e56277c82d19fd4da7b/raw/6158dd991b67284e9fc8d70b9d973efe87659d72/App.js) redone using React Bootstrap. ## Adding Flow Flow typing is currently [not supported out of the box](https://github.com/facebookincubator/create-react-app/issues/72) with the default `.flowconfig` generated by Flow. If you run it, you might get errors like this: ```js node_modules/fbjs/lib/Deferred.js.flow:60 60: Promise.prototype.done.apply(this._promise, arguments); ^^^^ property `done`. Property not found in 495: declare class Promise<+R> { ^ Promise. See lib: /private/tmp/flow/flowlib_34952d31/core.js:495 node_modules/fbjs/lib/shallowEqual.js.flow:29 29: return x !== 0 || 1 / (x: $FlowIssue) === 1 / (y: $FlowIssue); ^^^^^^^^^^ identifier `$FlowIssue`. Could not resolve name src/App.js:3 3: import logo from './logo.svg'; ^^^^^^^^^^^^ ./logo.svg. Required module not found src/App.js:4 4: import './App.css'; ^^^^^^^^^^^ ./App.css. Required module not found src/index.js:5 5: import './index.css'; ^^^^^^^^^^^^^ ./index.css. Required module not found ``` To fix this, change your `.flowconfig` to look like this: ```ini [libs] ./node_modules/fbjs/flow/lib [options] esproposal.class_static_fields=enable esproposal.class_instance_fields=enable module.name_mapper='^\(.*\)\.css$' -> 'react-scripts/config/flow/css' module.name_mapper='^\(.*\)\.\(jpg\|png\|gif\|eot\|otf\|webp\|svg\|ttf\|woff\|woff2\|mp4\|webm\)$' -> 'react-scripts/config/flow/file' suppress_type=$FlowIssue suppress_type=$FlowFixMe ``` Re-run flow, and you shouldn’t get any extra issues. If you later `eject`, you’ll need to replace `react-scripts` references with the `<PROJECT_ROOT>` placeholder, for example: ```ini module.name_mapper='^\(.*\)\.css$' -> '<PROJECT_ROOT>/config/flow/css' module.name_mapper='^\(.*\)\.\(jpg\|png\|gif\|eot\|otf\|webp\|svg\|ttf\|woff\|woff2\|mp4\|webm\)$' -> '<PROJECT_ROOT>/config/flow/file' ``` We will consider integrating more tightly with Flow in the future so that you don’t have to do this. ## Adding Custom Environment Variables >Note: this feature is available with `react-scripts@0.2.3` and higher. Your project can consume variables declared in your environment as if they were declared locally in your JS files. By default you will have `NODE_ENV` defined for you, and any other environment variables starting with `REACT_APP_`. These environment variables will be defined for you on `process.env`. For example, having an environment variable named `REACT_APP_SECRET_CODE` will be exposed in your JS as `process.env.REACT_APP_SECRET_CODE`, in addition to `process.env.NODE_ENV`. These environment variables can be useful for displaying information conditionally based on where the project is deployed or consuming sensitive data that lives outside of version control. First, you need to have environment variables defined, which can vary between OSes. For example, let's say you wanted to consume a secret defined in the environment inside a `<form>`: ```jsx render() { return ( <div> <small>You are running this application in <b>{process.env.NODE_ENV}</b> mode.</small> <form> <input type="hidden" defaultValue={process.env.REACT_APP_SECRET_CODE} /> </form> </div> ); } ``` The above form is looking for a variable called `REACT_APP_SECRET_CODE` from the environment. In order to consume this value, we need to have it defined in the environment: ### Windows (cmd.exe) ```cmd set REACT_APP_SECRET_CODE=abcdef&&npm start ``` (Note: the lack of whitespace is intentional.) ### Linux, OS X (Bash) ```bash REACT_APP_SECRET_CODE=abcdef npm start ``` > Note: Defining environment variables in this manner is temporary for the life of the shell session. Setting permanent environment variables is outside the scope of these docs. With our environment variable defined, we start the app and consume the values. Remember that the `NODE_ENV` variable will be set for you automatically. When you load the app in the browser and inspect the `<input>`, you will see its value set to `abcdef`, and the bold text will show the environment provided when using `npm start`: ```html <div> <small>You are running this application in <b>development</b> mode.</small> <form> <input type="hidden" value="abcdef" /> </form> </div> ``` Having access to the `NODE_ENV` is also useful for performing actions conditionally: ```js if (process.env.NODE_ENV !== 'production') { analytics.disable(); } ``` ## Integrating with a Node Backend Check out [this tutorial](https://www.fullstackreact.com/articles/using-create-react-app-with-a-server/) for instructions on integrating an app with a Node backend running on another port, and using `fetch()` to access it. You can find the companion GitHub repository [here](https://github.com/fullstackreact/food-lookup-demo). ## Proxying API Requests in Development >Note: this feature is available with `react-scripts@0.2.3` and higher. People often serve the front-end React app from the same host and port as their backend implementation. For example, a production setup might look like this after the app is deployed: ``` / - static server returns index.html with React app /todos - static server returns index.html with React app /api/todos - server handles any /api/* requests using the backend implementation ``` Such setup is **not** required. However, if you **do** have a setup like this, it is convenient to write requests like `fetch('/api/todos')` without worrying about redirecting them to another host or port during development. To tell the development server to proxy any unknown requests to your API server in development, add a `proxy` field to your `package.json`, for example: ```js "proxy": "http://localhost:4000", ``` This way, when you `fetch('/api/todos')` in development, the development server will recognize that it’s not a static asset, and will proxy your request to `http://localhost:4000/api/todos` as a fallback. Conveniently, this avoids [CORS issues](http://stackoverflow.com/questions/21854516/understanding-ajax-cors-and-security-considerations) and error messages like this in development: ``` Fetch API cannot load http://localhost:4000/api/todos. No 'Access-Control-Allow-Origin' header is present on the requested resource. Origin 'http://localhost:3000' is therefore not allowed access. If an opaque response serves your needs, set the request's mode to 'no-cors' to fetch the resource with CORS disabled. ``` Keep in mind that `proxy` only has effect in development (with `npm start`), and it is up to you to ensure that URLs like `/api/todos` point to the right thing in production. You don’t have to use the `/api` prefix. Any unrecognized request will be redirected to the specified `proxy`. Currently the `proxy` option only handles HTTP requests, and it won’t proxy WebSocket connections. If the `proxy` option is **not** flexible enough for you, alternatively you can: * Enable CORS on your server ([here’s how to do it for Express](http://enable-cors.org/server_expressjs.html)). * Use [environment variables](#adding-custom-environment-variables) to inject the right server host and port into your app. ## Deployment By default, Create React App produces a build assuming your app is hosted at the server root. To override this, specify the `homepage` in your `package.json`, for example: ```js "homepage": "http://mywebsite.com/relativepath", ``` This will let Create React App correctly infer the root path to use in the generated HTML file. ### Now See [this example](https://github.com/xkawi/create-react-app-now) for a zero-configuration single-command deployment with [now](https://zeit.co/now). ### Heroku Use the [Heroku Buildpack for Create React App](https://github.com/mars/create-react-app-buildpack). You can find instructions in [Deploying React with Zero Configuration](https://blog.heroku.com/deploying-react-with-zero-configuration). ### Surge Install the Surge CLI if you haven't already by running `npm install -g surge`. Run the `surge` command and log in you or create a new account. You just need to specify the *build* folder and your custom domain, and you are done. ```sh email: email@domain.com password: ******** project path: /path/to/project/build size: 7 files, 1.8 MB domain: create-react-app.surge.sh upload: [====================] 100%, eta: 0.0s propagate on CDN: [====================] 100% plan: Free users: email@domain.com IP Address: X.X.X.X Success! Project is published and running at create-react-app.surge.sh ``` Note that in order to support routers that use html5 `pushState` API, you may want to rename the `index.html` in your build folder to `200.html` before deploying to Surge. This [ensures that every URL falls back to that file](https://surge.sh/help/adding-a-200-page-for-client-side-routing). ### GitHub Pages >Note: this feature is available with `react-scripts@0.2.0` and higher. Open your `package.json` and add a `homepage` field: ```js "homepage": "http://myusername.github.io/my-app", ``` **The above step is important!** Create React App uses the `homepage` field to determine the root URL in the built HTML file. Now, whenever you run `npm run build`, you will see a cheat sheet with a sequence of commands to deploy to GitHub pages: ```sh git commit -am "Save local changes" git checkout -B gh-pages git add -f build git commit -am "Rebuild website" git filter-branch -f --prune-empty --subdirectory-filter build git push -f origin gh-pages git checkout - ``` You may copy and paste them, or put them into a custom shell script. You may also customize them for another hosting provider. Note that GitHub Pages doesn't support routers that use the HTML5 `pushState` history API under the hood (for example, React Router using `browserHistory`). This is because when there is a fresh page load for a url like `http://user.github.io/todomvc/todos/42`, where `/todos/42` is a frontend route, the GitHub Pages server returns 404 because it knows nothing of `/todos/42`. If you want to add a router to a project hosted on GitHub Pages, here are a couple of solutions: * You could switch from using HTML5 history API to routing with hashes. If you use React Router, you can switch to `hashHistory` for this effect, but the URL will be longer and more verbose (for example, `http://user.github.io/todomvc/#/todos/42?_k=yknaj`). [Read more](https://github.com/reactjs/react-router/blob/master/docs/guides/Histories.md#histories) about different history implementations in React Router. * Alternatively, you can use a trick to teach GitHub Pages to handle 404 by redirecting to your `index.html` page with a special redirect parameter. You would need to add a `404.html` file with the redirection code to the `build` folder before deploying your project, and you’ll need to add code handling the redirect parameter to `index.html`. You can find a detailed explanation of this technique [in this guide](https://github.com/rafrex/spa-github-pages). ## Something Missing? If you have ideas for more “How To” recipes that should be on this page, [let us know](https://github.com/facebookincubator/create-react-app/issues) or [contribute some!](https://github.com/facebookincubator/create-react-app/edit/master/template/README.md)

You would have noticed alot of channel getting popular on YouTube just by uploading “Reddit to Text-To-Speech” YouTube Videos. So I decided to create a program that can automate the process of receiving, generating and uploading these videos to YouTube with as little intervention as possible. It took me one month to complete this project. I divided the project to 3 scripts. The idea was to minimize as much manual intervention as possible and automate all the trivial tasks. However the process cannot be 100% automated. For example comments with links in them cannot be kept as quality of the video will be comprised due to the TTS. Additionally while a comment might have a large number of votes it could potentially be offensive and not safe for a YouTube video and thus must be removed. The thumbnail, while partially generated, must be edited in order to create any kind of appeal to viewers to click on your video. The same goes for the title of the video which must be clickbait-y in order to receive any attention. I have attempted to streamline the manual process with the client program and it takes me approximately 30 minutes to create 6 videos (the max that can be uploaded within 24 hours with the YouTube Data API).

A python package for text preprocessing task in natural language processing.

Many Natural Language Processing tasks rely on sentence boundary detection (SBD). Although amazing libraries like spacy provide state of the art SBD, they often depend on text extractors (e.g pdf text extractors or OCR). The quality of these extractors greatly influence the quality of SBD libraries and as a consequence, the performance of downstream models as well. To help address this problem, we fine-tuned a T5 model from the hugging face hub that attempts to reconstruct “broken sentences”

Poole, Mackworth & Goebel 1998, p. 1. Russell & Norvig 2003, p. 55. Definition of AI as the study of intelligent agents: Poole, Mackworth & Goebel (1998), which provides the version that is used in this article. These authors use the term "computational intelligence" as a synonym for artificial intelligence.[1] Russell & Norvig (2003) (who prefer the term "rational agent") and write "The whole-agent view is now widely accepted in the field".[2] Nilsson 1998 Legg & Hutter 2007 Russell & Norvig 2009, p. 2. McCorduck 2004, p. 204 Maloof, Mark. "Artificial Intelligence: An Introduction, p. 37" (PDF). georgetown.edu. Archived (PDF) from the original on 25 August 2018. "How AI Is Getting Groundbreaking Changes In Talent Management And HR Tech". Hackernoon. Archived from the original on 11 September 2019. Retrieved 14 February 2020. Schank, Roger C. (1991). "Where's the AI". AI magazine. Vol. 12 no. 4. p. 38. Russell & Norvig 2009. "AlphaGo – Google DeepMind". Archived from the original on 10 March 2016. Allen, Gregory (April 2020). "Department of Defense Joint AI Center - Understanding AI Technology" (PDF). AI.mil - The official site of the Department of Defense Joint Artificial Intelligence Center. Archived (PDF) from the original on 21 April 2020. Retrieved 25 April 2020. Optimism of early AI: * Herbert Simon quote: Simon 1965, p. 96 quoted in Crevier 1993, p. 109. * Marvin Minsky quote: Minsky 1967, p. 2 quoted in Crevier 1993, p. 109. Boom of the 1980s: rise of expert systems, Fifth Generation Project, Alvey, MCC, SCI: * McCorduck 2004, pp. 426–441 * Crevier 1993, pp. 161–162,197–203, 211, 240 * Russell & Norvig 2003, p. 24 * NRC 1999, pp. 210–211 * Newquist 1994, pp. 235–248 First AI Winter, Mansfield Amendment, Lighthill report * Crevier 1993, pp. 115–117 * Russell & Norvig 2003, p. 22 * NRC 1999, pp. 212–213 * Howe 1994 * Newquist 1994, pp. 189–201 Second AI winter: * McCorduck 2004, pp. 430–435 * Crevier 1993, pp. 209–210 * NRC 1999, pp. 214–216 * Newquist 1994, pp. 301–318 AI becomes hugely successful in the early 21st century * Clark 2015 Pamela McCorduck (2004, p. 424) writes of "the rough shattering of AI in subfields—vision, natural language, decision theory, genetic algorithms, robotics ... and these with own sub-subfield—that would hardly have anything to say to each other." This list of intelligent traits is based on the topics covered by the major AI textbooks, including: * Russell & Norvig 2003 * Luger & Stubblefield 2004 * Poole, Mackworth & Goebel 1998 * Nilsson 1998 Kolata 1982. Maker 2006. Biological intelligence vs. intelligence in general: Russell & Norvig 2003, pp. 2–3, who make the analogy with aeronautical engineering. McCorduck 2004, pp. 100–101, who writes that there are "two major branches of artificial intelligence: one aimed at producing intelligent behavior regardless of how it was accomplished, and the other aimed at modeling intelligent processes found in nature, particularly human ones." Kolata 1982, a paper in Science, which describes McCarthy's indifference to biological models. Kolata quotes McCarthy as writing: "This is AI, so we don't care if it's psychologically real".[19] McCarthy recently reiterated his position at the AI@50 conference where he said "Artificial intelligence is not, by definition, simulation of human intelligence".[20]. Neats vs. scruffies: * McCorduck 2004, pp. 421–424, 486–489 * Crevier 1993, p. 168 * Nilsson 1983, pp. 10–11 Symbolic vs. sub-symbolic AI: * Nilsson (1998, p. 7), who uses the term "sub-symbolic". General intelligence (strong AI) is discussed in popular introductions to AI: * Kurzweil 1999 and Kurzweil 2005 See the Dartmouth proposal, under Philosophy, below. McCorduck 2004, p. 34. McCorduck 2004, p. xviii. McCorduck 2004, p. 3. McCorduck 2004, pp. 340–400. This is a central idea of Pamela McCorduck's Machines Who Think. She writes: "I like to think of artificial intelligence as the scientific apotheosis of a venerable cultural tradition."[26] "Artificial intelligence in one form or another is an idea that has pervaded Western intellectual history, a dream in urgent need of being realized."[27] "Our history is full of attempts—nutty, eerie, comical, earnest, legendary and real—to make artificial intelligences, to reproduce what is the essential us—bypassing the ordinary means. Back and forth between myth and reality, our imaginations supplying what our workshops couldn't, we have engaged for a long time in this odd form of self-reproduction."[28] She traces the desire back to its Hellenistic roots and calls it the urge to "forge the Gods."[29] "Stephen Hawking believes AI could be mankind's last accomplishment". BetaNews. 21 October 2016. Archived from the original on 28 August 2017. Lombardo P, Boehm I, Nairz K (2020). "RadioComics – Santa Claus and the future of radiology". Eur J Radiol. 122 (1): 108771. doi:10.1016/j.ejrad.2019.108771. PMID 31835078. Ford, Martin; Colvin, Geoff (6 September 2015). "Will robots create more jobs than they destroy?". The Guardian. Archived from the original on 16 June 2018. Retrieved 13 January 2018. AI applications widely used behind the scenes: * Russell & Norvig 2003, p. 28 * Kurzweil 2005, p. 265 * NRC 1999, pp. 216–222 * Newquist 1994, pp. 189–201 AI in myth: * McCorduck 2004, pp. 4–5 * Russell & Norvig 2003, p. 939 AI in early science fiction. * McCorduck 2004, pp. 17–25 Formal reasoning: * Berlinski, David (2000). The Advent of the Algorithm. Harcourt Books. ISBN 978-0-15-601391-8. OCLC 46890682. Archived from the original on 26 July 2020. Retrieved 22 August 2020. Turing, Alan (1948), "Machine Intelligence", in Copeland, B. Jack (ed.), The Essential Turing: The ideas that gave birth to the computer age, Oxford: Oxford University Press, p. 412, ISBN 978-0-19-825080-7 Russell & Norvig 2009, p. 16. Dartmouth conference: * McCorduck 2004, pp. 111–136 * Crevier 1993, pp. 47–49, who writes "the conference is generally recognized as the official birthdate of the new science." * Russell & Norvig 2003, p. 17, who call the conference "the birth of artificial intelligence." * NRC 1999, pp. 200–201 McCarthy, John (1988). "Review of The Question of Artificial Intelligence". Annals of the History of Computing. 10 (3): 224–229., collected in McCarthy, John (1996). "10. Review of The Question of Artificial Intelligence". Defending AI Research: A Collection of Essays and Reviews. CSLI., p. 73, "[O]ne of the reasons for inventing the term "artificial intelligence" was to escape association with "cybernetics". Its concentration on analog feedback seemed misguided, and I wished to avoid having either to accept Norbert (not Robert) Wiener as a guru or having to argue with him." Hegemony of the Dartmouth conference attendees: * Russell & Norvig 2003, p. 17, who write "for the next 20 years the field would be dominated by these people and their students." * McCorduck 2004, pp. 129–130 Russell & Norvig 2003, p. 18. Schaeffer J. (2009) Didn't Samuel Solve That Game?. In: One Jump Ahead. Springer, Boston, MA Samuel, A. L. (July 1959). "Some Studies in Machine Learning Using the Game of Checkers". IBM Journal of Research and Development. 3 (3): 210–229. CiteSeerX 10.1.1.368.2254. doi:10.1147/rd.33.0210. "Golden years" of AI (successful symbolic reasoning programs 1956–1973): * McCorduck 2004, pp. 243–252 * Crevier 1993, pp. 52–107 * Moravec 1988, p. 9 * Russell & Norvig 2003, pp. 18–21 The programs described are Arthur Samuel's checkers program for the IBM 701, Daniel Bobrow's STUDENT, Newell and Simon's Logic Theorist and Terry Winograd's SHRDLU. DARPA pours money into undirected pure research into AI during the 1960s: * McCorduck 2004, p. 131 * Crevier 1993, pp. 51, 64–65 * NRC 1999, pp. 204–205 AI in England: * Howe 1994 Lighthill 1973. Expert systems: * ACM 1998, I.2.1 * Russell & Norvig 2003, pp. 22–24 * Luger & Stubblefield 2004, pp. 227–331 * Nilsson 1998, chpt. 17.4 * McCorduck 2004, pp. 327–335, 434–435 * Crevier 1993, pp. 145–62, 197–203 * Newquist 1994, pp. 155–183 Mead, Carver A.; Ismail, Mohammed (8 May 1989). Analog VLSI Implementation of Neural Systems (PDF). The Kluwer International Series in Engineering and Computer Science. 80. Norwell, MA: Kluwer Academic Publishers. doi:10.1007/978-1-4613-1639-8. ISBN 978-1-4613-1639-8. Archived from the original (PDF) on 6 November 2019. Retrieved 24 January 2020. Formal methods are now preferred ("Victory of the neats"): * Russell & Norvig 2003, pp. 25–26 * McCorduck 2004, pp. 486–487 McCorduck 2004, pp. 480–483. Markoff 2011. 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Cognitive Systems Research. 48: 39–55. doi:10.1016/j.cogsys.2017.05.001. hdl:2318/1665207. S2CID 206868967. Problem solving, puzzle solving, game playing and deduction: * Russell & Norvig 2003, chpt. 3–9, * Poole, Mackworth & Goebel 1998, chpt. 2,3,7,9, * Luger & Stubblefield 2004, chpt. 3,4,6,8, * Nilsson 1998, chpt. 7–12 Uncertain reasoning: * Russell & Norvig 2003, pp. 452–644, * Poole, Mackworth & Goebel 1998, pp. 345–395, * Luger & Stubblefield 2004, pp. 333–381, * Nilsson 1998, chpt. 19 Psychological evidence of sub-symbolic reasoning: * Wason & Shapiro (1966) showed that people do poorly on completely abstract problems, but if the problem is restated to allow the use of intuitive social intelligence, performance dramatically improves. (See Wason selection task) * Kahneman, Slovic & Tversky (1982) have shown that people are terrible at elementary problems that involve uncertain reasoning. (See list of cognitive biases for several examples). * Lakoff & Núñez (2000) have controversially argued that even our skills at mathematics depend on knowledge and skills that come from "the body", i.e. sensorimotor and perceptual skills. (See Where Mathematics Comes From) Knowledge representation: * ACM 1998, I.2.4, * Russell & Norvig 2003, pp. 320–363, * Poole, Mackworth & Goebel 1998, pp. 23–46, 69–81, 169–196, 235–277, 281–298, 319–345, * Luger & Stubblefield 2004, pp. 227–243, * Nilsson 1998, chpt. 18 Knowledge engineering: * Russell & Norvig 2003, pp. 260–266, * Poole, Mackworth & Goebel 1998, pp. 199–233, * Nilsson 1998, chpt. ≈17.1–17.4 Representing categories and relations: Semantic networks, description logics, inheritance (including frames and scripts): * Russell & Norvig 2003, pp. 349–354, * Poole, Mackworth & Goebel 1998, pp. 174–177, * Luger & Stubblefield 2004, pp. 248–258, * Nilsson 1998, chpt. 18.3 Representing events and time:Situation calculus, event calculus, fluent calculus (including solving the frame problem): * Russell & Norvig 2003, pp. 328–341, * Poole, Mackworth & Goebel 1998, pp. 281–298, * Nilsson 1998, chpt. 18.2 Causal calculus: * Poole, Mackworth & Goebel 1998, pp. 335–337 Representing knowledge about knowledge: Belief calculus, modal logics: * Russell & Norvig 2003, pp. 341–344, * Poole, Mackworth & Goebel 1998, pp. 275–277 Sikos, Leslie F. (June 2017). Description Logics in Multimedia Reasoning. Cham: Springer. doi:10.1007/978-3-319-54066-5. ISBN 978-3-319-54066-5. S2CID 3180114. Archived from the original on 29 August 2017. Ontology: * Russell & Norvig 2003, pp. 320–328 Smoliar, Stephen W.; Zhang, HongJiang (1994). "Content based video indexing and retrieval". IEEE Multimedia. 1 (2): 62–72. doi:10.1109/93.311653. S2CID 32710913. Neumann, Bernd; Möller, Ralf (January 2008). "On scene interpretation with description logics". Image and Vision Computing. 26 (1): 82–101. doi:10.1016/j.imavis.2007.08.013. Kuperman, G. J.; Reichley, R. M.; Bailey, T. C. (1 July 2006). "Using Commercial Knowledge Bases for Clinical Decision Support: Opportunities, Hurdles, and Recommendations". Journal of the American Medical Informatics Association. 13 (4): 369–371. doi:10.1197/jamia.M2055. PMC 1513681. PMID 16622160. MCGARRY, KEN (1 December 2005). "A survey of interestingness measures for knowledge discovery". The Knowledge Engineering Review. 20 (1): 39–61. doi:10.1017/S0269888905000408. S2CID 14987656. Bertini, M; Del Bimbo, A; Torniai, C (2006). "Automatic annotation and semantic retrieval of video sequences using multimedia ontologies". MM '06 Proceedings of the 14th ACM international conference on Multimedia. 14th ACM international conference on Multimedia. Santa Barbara: ACM. pp. 679–682. Qualification problem: * McCarthy & Hayes 1969 * Russell & Norvig 2003[page needed] While McCarthy was primarily concerned with issues in the logical representation of actions, Russell & Norvig 2003 apply the term to the more general issue of default reasoning in the vast network of assumptions underlying all our commonsense knowledge. Default reasoning and default logic, non-monotonic logics, circumscription, closed world assumption, abduction (Poole et al. places abduction under "default reasoning". Luger et al. places this under "uncertain reasoning"): * Russell & Norvig 2003, pp. 354–360, * Poole, Mackworth & Goebel 1998, pp. 248–256, 323–335, * Luger & Stubblefield 2004, pp. 335–363, * Nilsson 1998, ~18.3.3 Breadth of commonsense knowledge: * Russell & Norvig 2003, p. 21, * Crevier 1993, pp. 113–114, * Moravec 1988, p. 13, * Lenat & Guha 1989 (Introduction) Dreyfus & Dreyfus 1986. Gladwell 2005. Expert knowledge as embodied intuition: * Dreyfus & Dreyfus 1986 (Hubert Dreyfus is a philosopher and critic of AI who was among the first to argue that most useful human knowledge was encoded sub-symbolically. See Dreyfus' critique of AI) * Gladwell 2005 (Gladwell's Blink is a popular introduction to sub-symbolic reasoning and knowledge.) * Hawkins & Blakeslee 2005 (Hawkins argues that sub-symbolic knowledge should be the primary focus of AI research.) Planning: * ACM 1998, ~I.2.8, * Russell & Norvig 2003, pp. 375–459, * Poole, Mackworth & Goebel 1998, pp. 281–316, * Luger & Stubblefield 2004, pp. 314–329, * Nilsson 1998, chpt. 10.1–2, 22 Information value theory: * Russell & Norvig 2003, pp. 600–604 Classical planning: * Russell & Norvig 2003, pp. 375–430, * Poole, Mackworth & Goebel 1998, pp. 281–315, * Luger & Stubblefield 2004, pp. 314–329, * Nilsson 1998, chpt. 10.1–2, 22 Planning and acting in non-deterministic domains: conditional planning, execution monitoring, replanning and continuous planning: * Russell & Norvig 2003, pp. 430–449 Multi-agent planning and emergent behavior: * Russell & Norvig 2003, pp. 449–455 Turing 1950. Solomonoff 1956. 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Archived from the original on 11 June 2020. Retrieved 11 June 2020. Machine perception: * Russell & Norvig 2003, pp. 537–581, 863–898 * Nilsson 1998, ~chpt. 6 Speech recognition: * ACM 1998, ~I.2.7 * Russell & Norvig 2003, pp. 568–578 Object recognition: * Russell & Norvig 2003, pp. 885–892 Computer vision: * ACM 1998, I.2.10 * Russell & Norvig 2003, pp. 863–898 * Nilsson 1998, chpt. 6 Robotics: * ACM 1998, I.2.9, * Russell & Norvig 2003, pp. 901–942, * Poole, Mackworth & Goebel 1998, pp. 443–460 Moving and configuration space: * Russell & Norvig 2003, pp. 916–932 Tecuci 2012. Robotic mapping (localization, etc): * Russell & Norvig 2003, pp. 908–915 Cadena, Cesar; Carlone, Luca; Carrillo, Henry; Latif, Yasir; Scaramuzza, Davide; Neira, Jose; Reid, Ian; Leonard, John J. (December 2016). "Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age". IEEE Transactions on Robotics. 32 (6): 1309–1332. arXiv:1606.05830. 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Retrieved 26 April 2018. Domingos 2015. Artificial brain arguments: AI requires a simulation of the operation of the human brain * Russell & Norvig 2003, p. 957 * Crevier 1993, pp. 271 and 279 A few of the people who make some form of the argument: * Moravec 1988 * Kurzweil 2005, p. 262 * Hawkins & Blakeslee 2005 The most extreme form of this argument (the brain replacement scenario) was put forward by Clark Glymour in the mid-1970s and was touched on by Zenon Pylyshyn and John Searle in 1980. Goertzel, Ben; Lian, Ruiting; Arel, Itamar; de Garis, Hugo; Chen, Shuo (December 2010). "A world survey of artificial brain projects, Part II: Biologically inspired cognitive architectures". Neurocomputing. 74 (1–3): 30–49. doi:10.1016/j.neucom.2010.08.012. Nilsson 1983, p. 10. Nils Nilsson writes: "Simply put, there is wide disagreement in the field about what AI is all about."[163] AI's immediate precursors: * McCorduck 2004, pp. 51–107 * Crevier 1993, pp. 27–32 * Russell & Norvig 2003, pp. 15, 940 * Moravec 1988, p. 3 Haugeland 1985, pp. 112–117 The most dramatic case of sub-symbolic AI being pushed into the background was the devastating critique of perceptrons by Marvin Minsky and Seymour Papert in 1969. See History of AI, AI winter, or Frank Rosenblatt. Cognitive simulation, Newell and Simon, AI at CMU (then called Carnegie Tech): * McCorduck 2004, pp. 139–179, 245–250, 322–323 (EPAM) * Crevier 1993, pp. 145–149 Soar (history): * McCorduck 2004, pp. 450–451 * Crevier 1993, pp. 258–263 McCarthy and AI research at SAIL and SRI International: * McCorduck 2004, pp. 251–259 * Crevier 1993 AI research at Edinburgh and in France, birth of Prolog: * Crevier 1993, pp. 193–196 * Howe 1994 AI at MIT under Marvin Minsky in the 1960s : * McCorduck 2004, pp. 259–305 * Crevier 1993, pp. 83–102, 163–176 * Russell & Norvig 2003, p. 19 Cyc: * McCorduck 2004, p. 489, who calls it "a determinedly scruffy enterprise" * Crevier 1993, pp. 239–243 * Russell & Norvig 2003, p. 363−365 * Lenat & Guha 1989 Knowledge revolution: * McCorduck 2004, pp. 266–276, 298–300, 314, 421 * Russell & Norvig 2003, pp. 22–23 Frederick, Hayes-Roth; William, Murray; Leonard, Adelman. "Expert systems". AccessScience. doi:10.1036/1097-8542.248550. Embodied approaches to AI: * McCorduck 2004, pp. 454–462 * Brooks 1990 * Moravec 1988 Weng et al. 2001. Lungarella et al. 2003. Asada et al. 2009. Oudeyer 2010. Revival of connectionism: * Crevier 1993, pp. 214–215 * Russell & Norvig 2003, p. 25 Computational intelligence * IEEE Computational Intelligence Society Archived 9 May 2008 at the Wayback Machine Hutson, Matthew (16 February 2018). "Artificial intelligence faces reproducibility crisis". Science. pp. 725–726. Bibcode:2018Sci...359..725H. doi:10.1126/science.359.6377.725. Archived from the original on 29 April 2018. Retrieved 28 April 2018. Norvig 2012. Langley 2011. Katz 2012. The intelligent agent paradigm: * Russell & Norvig 2003, pp. 27, 32–58, 968–972 * Poole, Mackworth & Goebel 1998, pp. 7–21 * Luger & Stubblefield 2004, pp. 235–240 * Hutter 2005, pp. 125–126 The definition used in this article, in terms of goals, actions, perception and environment, is due to Russell & Norvig (2003). Other definitions also include knowledge and learning as additional criteria. Agent architectures, hybrid intelligent systems: * Russell & Norvig (2003, pp. 27, 932, 970–972) * Nilsson (1998, chpt. 25) Hierarchical control system: * Albus 2002 Lieto, Antonio; Lebiere, Christian; Oltramari, Alessandro (May 2018). "The knowledge level in cognitive architectures: Current limitations and possibile developments". Cognitive Systems Research. 48: 39–55. doi:10.1016/j.cogsys.2017.05.001. hdl:2318/1665207. S2CID 206868967. Lieto, Antonio; Bhatt, Mehul; Oltramari, Alessandro; Vernon, David (May 2018). "The role of cognitive architectures in general artificial intelligence". Cognitive Systems Research. 48: 1–3. doi:10.1016/j.cogsys.2017.08.003. hdl:2318/1665249. S2CID 36189683. Russell & Norvig 2009, p. 1. White Paper: On Artificial Intelligence - A European approach to excellence and trust (PDF). Brussels: European Commission. 2020. p. 1. Archived (PDF) from the original on 20 February 2020. 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"Social media 'outstrips TV' as news source for young people". BBC News. Archived from the original on 24 June 2016. Smith, Mark (22 July 2016). "So you think you chose to read this article?". BBC News. Archived from the original on 25 July 2016. Brown, Eileen. "Half of Americans do not believe deepfake news could target them online". ZDNet. Archived from the original on 6 November 2019. Retrieved 3 December 2019. The Turing test: Turing's original publication: * Turing 1950 Historical influence and philosophical implications: * Haugeland 1985, pp. 6–9 * Crevier 1993, p. 24 * McCorduck 2004, pp. 70–71 * Russell & Norvig 2003, pp. 2–3 and 948 Dartmouth proposal: * McCarthy et al. 1955 (the original proposal) * Crevier 1993, p. 49 (historical significance) The physical symbol systems hypothesis: * Newell & Simon 1976, p. 116 * McCorduck 2004, p. 153 * Russell & Norvig 2003, p. 18 Dreyfus 1992, p. 156. Dreyfus criticized the necessary condition of the physical symbol system hypothesis, which he called the "psychological assumption": "The mind can be viewed as a device operating on bits of information according to formal rules."[206] Dreyfus' critique of artificial intelligence: * Dreyfus 1972, Dreyfus & Dreyfus 1986 * Crevier 1993, pp. 120–132 * McCorduck 2004, pp. 211–239 * Russell & Norvig 2003, pp. 950–952, Gödel 1951: in this lecture, Kurt Gödel uses the incompleteness theorem to arrive at the following disjunction: (a) the human mind is not a consistent finite machine, or (b) there exist Diophantine equations for which it cannot decide whether solutions exist. Gödel finds (b) implausible, and thus seems to have believed the human mind was not equivalent to a finite machine, i.e., its power exceeded that of any finite machine. He recognized that this was only a conjecture, since one could never disprove (b). Yet he considered the disjunctive conclusion to be a "certain fact". The Mathematical Objection: * Russell & Norvig 2003, p. 949 * McCorduck 2004, pp. 448–449 Making the Mathematical Objection: * Lucas 1961 * Penrose 1989 Refuting Mathematical Objection: * Turing 1950 under "(2) The Mathematical Objection" * Hofstadter 1979 Background: * Gödel 1931, Church 1936, Kleene 1935, Turing 1937 Graham Oppy (20 January 2015). "Gödel's Incompleteness Theorems". Stanford Encyclopedia of Philosophy. Archived from the original on 22 April 2016. Retrieved 27 April 2016. These Gödelian anti-mechanist arguments are, however, problematic, and there is wide consensus that they fail. Stuart J. Russell; Peter Norvig (2010). "26.1.2: Philosophical Foundations/Weak AI: Can Machines Act Intelligently?/The mathematical objection". Artificial Intelligence: A Modern Approach (3rd ed.). Upper Saddle River, NJ: Prentice Hall. ISBN 978-0-13-604259-4. even if we grant that computers have limitations on what they can prove, there is no evidence that humans are immune from those limitations. Mark Colyvan. An introduction to the philosophy of mathematics. Cambridge University Press, 2012. From 2.2.2, 'Philosophical significance of Gödel's incompleteness results': "The accepted wisdom (with which I concur) is that the Lucas-Penrose arguments fail." Iphofen, Ron; Kritikos, Mihalis (3 January 2019). "Regulating artificial intelligence and robotics: ethics by design in a digital society". Contemporary Social Science: 1–15. doi:10.1080/21582041.2018.1563803. ISSN 2158-2041. "Ethical AI Learns Human Rights Framework". Voice of America. Archived from the original on 11 November 2019. Retrieved 10 November 2019. Crevier 1993, pp. 132–144. In the early 1970s, Kenneth Colby presented a version of Weizenbaum's ELIZA known as DOCTOR which he promoted as a serious therapeutic tool.[216] Joseph Weizenbaum's critique of AI: * Weizenbaum 1976 * Crevier 1993, pp. 132–144 * McCorduck 2004, pp. 356–373 * Russell & Norvig 2003, p. 961 Weizenbaum (the AI researcher who developed the first chatterbot program, ELIZA) argued in 1976 that the misuse of artificial intelligence has the potential to devalue human life. Wendell Wallach (2010). Moral Machines, Oxford University Press. Wallach, pp 37–54. Wallach, pp 55–73. Wallach, Introduction chapter. Michael Anderson and Susan Leigh Anderson (2011), Machine Ethics, Cambridge University Press. "Machine Ethics". aaai.org. Archived from the original on 29 November 2014. Rubin, Charles (Spring 2003). "Artificial Intelligence and Human Nature". The New Atlantis. 1: 88–100. Archived from the original on 11 June 2012. Brooks, Rodney (10 November 2014). "artificial intelligence is a tool, not a threat". Archived from the original on 12 November 2014. "Stephen Hawking, Elon Musk, and Bill Gates Warn About Artificial Intelligence". Observer. 19 August 2015. Archived from the original on 30 October 2015. Retrieved 30 October 2015. Chalmers, David (1995). "Facing up to the problem of consciousness". Journal of Consciousness Studies. 2 (3): 200–219. Archived from the original on 8 March 2005. Retrieved 11 October 2018. See also this link Archived 8 April 2011 at the Wayback Machine Horst, Steven, (2005) "The Computational Theory of Mind" Archived 11 September 2018 at the Wayback Machine in The Stanford Encyclopedia of Philosophy Searle 1980, p. 1. This version is from Searle (1999), and is also quoted in Dennett 1991, p. 435. Searle's original formulation was "The appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to understand and have other cognitive states." [230] Strong AI is defined similarly by Russell & Norvig (2003, p. 947): "The assertion that machines could possibly act intelligently

Claude 3 API PHP Package: Seamlessly integrate Anthropic's Claude 3 AI into your PHP projects. Features simple chat interface, advanced message handling, vision capabilities, streaming support, and tool usage. Ideal for text processing, image analysis, and complex AI tasks. Fully tested and error-handled.

The objective of this project is to scrape a corpus of news articles from a set of web pages, pre-process the corpus, and then to apply unsupervised clustering algorithms to explore and summarise the contents of the corpus. Part 1. Text Data Scraping This part of the project should be implemented as a Python script 1. Identify the URLs for all news articles listed on the website: http://mlg.ucd.ie/modules/COMP41680/news/index.html 2. Retrieve all web pages corresponding to these article URLs. 3. From the web pages, extract the main body text containing the content of each news article. Save the body of each article as plain text. Part 2. Corpus Exploration Tasks to be completed in your IPython notebook: 1. Load the text corpus generated in Part 1. Apply any appropriate pre-processing steps and construct a document-term matrix representation of the corpus. 2. Summarise the overall corpus by identifying the most characteristic terms and phrases in the corpus. 3. Apply two alternative clustering algorithms of your choice to the document-term matrix to produce clusters of related documents. This might require applying each algorithm several times with different parameter values. 4. For each clustering generated in Step 3, summarise the contents of the clusters. Based on your summary, suggest a topic/theme for each cluster.

SEIS 665 Assignment 2: Linux & Git Overview This week we will focus on becoming familiar with launching a Linux server and working with some basic Linux and Git commands. We will use AWS to launch and host the Linux server. AWS might seem a little confusing at this point. Don’t worry, we will gain much more hands-on experience with AWS throughout the course. The goal is to get you comfortable working with the technology and not overwhelm you with all the details. Requirements You need to have a personal AWS account and GitHub account for this assignment. You should also read the Git Hands-on Guide and Linux Hands-on Guide before beginning this exercise. A word about grading One of the key DevOps practices we learn about in this class is the use of automation to increase the speed and repeatability of processes. Automation is utilized during the assignment grading process to review and assess your work. It’s important that you follow the instructions in each assignment and type in required files and resources with the proper names. All names are case sensitive, so a name like "Web1" is not the same as "web1". If you misspell a name, use the wrong case, or put a file in the wrong directory location you will lose points on your assignment. This is the easiest way to lose points, and also the most preventable. You should always double-check your work to make sure it accurately reflects the requirements specified in the assignment. You should always carefully review the content of your files before submitting your assignment. The assignment Let’s get started! Create GitHub repository The first step in the assignment is to setup a Git repository on GitHub. We will use a special solution called GitHub Classroom for this course which automates the process of setting up student assignment repositories. Here are the basic steps: Click on the following link to open Assignment 2 on the GitHub Classroom site: https://classroom.github.com/a/K4zcVmX- (Links to an external site.)Links to an external site. Click on the Accept this assignment button. GitHub Classroom will provide you with a URL (https) to access the assignment repository. Either copy this address to your clipboard or write it down somewhere. You will need to use this address to set up the repository on a Linux server. Example: https://github.com/UST-SEIS665/hw2-seis665-02-spring2019-<your github id>.git At this point your new repository to ready to use. The repository is currently empty. We will put some content in there soon! Launch Linux server The second step in the assignment is to launch a Linux server using AWS EC2. The server should have the following characteristics: Amazon Linux 2 AMI 64-bit (usually the first option listed) Located in a U.S. region (us-east-1) t2.micro instance type All default instance settings (storage, vpm, security group, etc.) I’ve shown you how to launch EC2 instances in class. You can review it on Canvas. Once you launch the new server, it may take a few minutes to provision. Log into server The next step is to log into the Linux server using a terminal program with a secure shell (SSH) support. You can use iTerm2 (Links to an external site.)Links to an external site. on a Mac and GitBash/PuTTY (Links to an external site.)Links to an external site. on a PC. You will need to have the private server key and the public IP address before attempting to log into the server. The server key is basically your password. If you lose it, you will need to terminate the existing instance and launch a new server. I recommend reusing the same key when launching new servers throughout the class. Note, I make this recommendation to make the learning process easier and not because it is a common security practice. I’ve shown you how to use a terminal application to log into the instance using a Windows desktop. Your personal computer or lab computer may be running a different OS version, but the process is still very similar. You can review the videos on the Canvas. Working with Linux If you’ve made it this far, congratulations! You’ve made it over the toughest hurdle. By the end of this course, I promise you will be able to launch and log into servers in your sleep. You should be looking at a login screen that looks something like this: Last login: Mon Mar 21 21:17:54 2016 from 174-20-199-194.mpls.qwest.net __| __|_ ) _| ( / Amazon Linux AMI ___|\___|___| https://aws.amazon.com/amazon-linux-ami/2015.09-release-notes/ 8 package(s) needed for security, out of 17 available Run "sudo yum update" to apply all updates. ec2-user@ip-172-31-15-26 ~]$ Your terminal cursor is sitting at the shell prompt, waiting for you to type in your first command. Remember the shell? It is a really cool program that lets you start other programs and manage services on the Linux system. The rest of this assignment will be spent working with the shell. Note, when you are asked to type in a command in the steps below, don’t type in the dollar-sign ($) character. This is just meant to represent the command prompt. The actual commands are represented by the characters to the right of the command prompt. Let’s start by asking the shell for some help. Type in: $ help The shell provides you with a list of commands you can run along with possible command options. Next, check out one of the pages in the built-in manual: $ man ls A man page will appear with information on how to use the ls command. This command is used to list the contents of file directories. Either space through the contents of the man page or hit q to exit. Most of the core Linux commands have man pages available. But honestly, some of these man pages are a bit hard to understand. Sometimes your best bet is to search on Google if you are trying to figure out how to use a specific command. When you initially log into Linux, the system places you in your home directory. Each user on the system has a separate home directory. Let’s see where your home directory is located: $ pwd The response should be /home/ec2-user. The pwd command is handy to remember if you ever forget what file directory you are currently located in. If you recall from the Linux Hands-on Guide, this directory is also your current working directory. Type in: $ cd / The cd command let’s you change to a new working directory on the server. In this case, we changed to the root (/) directory. This is the parent of all the other directories on the file system. Type in: $ ls The ls command lists the contents of the current directory. As you can see, root directory contains many other directories. You will become familiar with these directories over time. The ls command provides a very basic directory listing. You need to supply the command with some options if you want to see more detailed information. Type in: $ ls -la See how this command provides you with much more detailed information about the files and directories? You can use this detailed listing to see the owner, group, and access control list settings for each file or directory. Do you see any files listed? Remember, the first character in the access control list column denotes whether a listed item is a file or a directory. You probably see a couple files with names like .autofsck. How come you didn’t see this file when you typed in the lscommand without any options? (Try to run this command again to convince yourself.) Files names that start with a period are called hidden files. These files won’t appear on normal directory listings. Type in: $ cd /var Then, type in: $ ls You will see a directory listing for the /var directory. Next, type in: $ ls .. Huh. This directory listing looks the same as the earlier root directory listing. When you use two periods (..) in a directory path that means you are referring to the parent directory of the current directory. Just think of the two dots as meaning the directory above the current directory. Now, type in: $ cd ~ $ pwd Whoa. We’re back at our home directory again. The tilde character (~) is another one of those handy little directory path shortcuts. It always refers to our personal home directory. Keep in mind that since every user has their own home directory, the tilde shortcut will refer to a unique directory for each logged-in user. Most students are used to navigating a file system by clicking a mouse in nested graphical folders. When they start using a command-line to navigate a file system, they sometimes get confused and lose track of their current position in the file system. Remember, you can always use the pwd command to quickly figure out what directory you are currently working in. Let’s make some changes to the file system. We can easily make our own directories on the file system. Type: mkdir test Now type: ls Cool, there’s our new test directory. Let’s pretend we don’t like that directory name and delete it. Type: rmdir test Now it’s gone. How can you be sure? You should know how to check to see if the directory still exists at this point. Go ahead and check. Let’s create another directory. Type in: $ mkdir documents Next, change to the new directory: $ cd documents Did you notice that your command prompt displays the name of the current directory? Something like: [ec2-user@ip-172-31-15-26 documents]$. Pretty handy, huh? Okay, let’s create our first file in the documents directory. This is just an empty file for training purposes. Type in: $ touch paper.txt Check to see that the new file is in the directory. Now, go back to the previous directory. Remember the double dot shortcut? $ cd .. Okay, we don’t like our documents directory any more. Let’s blow it away. Type in: $ rmdir documents Uh oh. The shell didn’t like that command because the directory isn’t empty. Let’s change back into the documents directory. But this time don’t type in the full name of the directory. You can let shell auto-completion do the typing for you. Type in the first couple characters of the directory name and then hit the tab key: $ cd doc<tab> You should use the tab auto-completion feature often. It saves typing and makes working with the Linux file system much much easier. Tab is your friend. Now, remove the file by typing: $ rm paper.txt Did you try to use the tab key instead of typing in the whole file name? Check to make sure the file was deleted from the directory. Next, create a new file: $ touch file1 We like file1 so much that we want to make a backup copy. Type: $ cp file1 file1-backup Check to make sure the new backup copy was created. We don’t really like the name of that new file, so let’s rename it. Type: $ mv file1-backup backup Moving a file to the same directory and giving it a new name is basically the same thing as renaming it. We could have moved it to a different directory if we wanted. Let’s list all of the files in the current directory that start with the letter f: $ ls f* Using wildcard pattern matching in file commands is really useful if you want the command to impact or filter a group of files. Now, go up one directory to the parent directory (remember the double dot shortcut?) We tried to remove the documents directory earlier when it had files in it. Obviously that won’t work again. However, we can use a more powerful command to destroy the directory and vanquish its contents. Behold, the all powerful remove command: $ rm -fr documents Did you remember to use auto-completion when typing in documents? This command and set of options forcibly removes the directory and its contents. It’s a dangerous command wielded by the mightiest Linux wizards. Okay, maybe that’s a bit of an exaggeration. Just be careful with it. Check to make sure the documents directory is gone before proceeding. Let’s continue. Change to the directory /var and make a directory called test. Ugh. Permission denied. We created this darn Linux server and we paid for it. Shouldn’t we be able to do anything we want on it? You logged into the system as a user called ec2-user. While this user can create and manage files in its home directory, it cannot change files all across the system. At least it can’t as a normal user. The ec2-user is a member of the root group, so it can escalate its privileges to super-user status when necessary. Let’s try it: $ sudo mkdir test Check to make sure the directory exists now. Using sudo we can execute commands as a super-user. We can do anything we want now that we know this powerful new command. Go ahead and delete the test directory. Did you remember to use sudo before the rmdir command? Check to make sure the directory is gone. You might be asking yourself the question: why can we list the contents of the /var directory but not make changes? That’s because all users have read access to the /var directory and the ls command is a read function. Only the root users or those acting as a super-user can write changes to the directory. Let’s go back to our home directory: $ cd ~ Editing text files is a really common task on Linux systems because many of the application configuration files are text files. We can create a text file by using a text editor. Type in: $ nano myfile.conf The shell starts up the nano text editor and places your terminal cursor in the editing screen. Nano is a simple text-based word processor. Type in a few lines of text. When you’re done writing your novel, hit ctrl-x and answer y to the prompt to save your work. Finally, hit enter to save the text to the filename you specified. Check to see that your file was saved in the directory. You can take a look at the contents of your file by typing: $ cat myfile.conf The cat command displays your text file content on the terminal screen. This command works fine for displaying small text files. But if your file is hundreds of lines long, the content will scroll down your terminal screen so fast that you won’t be able to easily read it. There’s a better way to view larger text files. Type in: $ less myfile.conf The less command will page the display of a text file, allowing you to page through the contents of the file using the space bar. Your text file is probably too short to see the paging in action though. Hit q to quit out of the less text viewer. Hit the up-arrow key on your keyboard a few times until the commmand nano myfile.conf appears next to your command prompt. Cool, huh? The up-arrow key allows you to replay a previously run command. Linux maintains a list of all the commands you have run since you logged into the server. This is called the command history. It’s a really useful feature if you have to re-run a complex command again. Now, hit ctrl-c. This cancels whatever command is displayed on the command line. Type in the following command to create a couple empty files in the directory: $ touch file1 file2 file3 Confirm that the files were created. Some commands, like touch. allow you to specify multiple files as arguments. You will find that Linux commands have all kinds of ways to make tasks more efficient like this. Throughout this assignment, we have been running commands and viewing results on the terminal screen. The screen is the standard place for commands to output results. It’s known as the standard out (stdout). However, it’s really useful to output results to the file system sometimes. Type in: $ ls > listing.txt Take a look at the directory listing now. You just created a new file. View the contents of the listing.txt file. What do you see? Instead of sending the output from the ls command to the screen we sent it to a text file. Let’s try another one. Type: $ cat myfile.conf > listing.txt Take a look at the contents of the listing.txt file again. It looks like your myfile.conf file now. It’s like you made a copy of it. But what happened to the previous content in the listing.txt file? When you redirect the output of a command using the right angle-bracket character (>), the output overwrites the existing file. Type this command in: $ cat myfile.conf >> listing.txt Now look at the contents of the listing.txt file. You should see your original content displayed twice. When you use two angle-bracket characters in the commmand the output appends (or adds to) the file instead of overwriting it. We redirected the output from a command to a text file. It’s also possible to redirect the input to a command. Typically we use a keyboard to provide input, but sometimes it makes more sense to input a file to a command. For example, how many words are in your new listing.txt file? Let’s find out. Type in: $ wc -w < listing.txt Did you get a number? This command inputs the listing.txt file into a word count program called wc. Type in the command: $ ls /usr/bin The terminal screen probably scrolled quickly as filenames flashed by. The /usr/bin directory holds quite a few files. It would be nice if we could page through the contents of this directory. Well, we can. We can use a special shell feature called pipes. In previous steps, we redirected I/O using the file system. Pipes allow us to redirect I/O between programs. We can redirect the output from one program into another. Type in: $ ls /usr/bin | less Now the directory listing is paged. Hit the spacebar to page through the listing. The pipe, represented by a vertical bar character (|), takes the output from the ls command and redirects it to the less command where the resulting output is paged. Pipes are super powerful and used all the time by savvy Linux operators. Hit the q key to quit the paginated directory listing command. Working with shell scripts Now things are going to get interesting. We’ve been manually typing in commands throughout this exercise. If we were running a set of repetitive tasks, we would want to automate the process as much as possible. The shell makes it really easy to automate tasks using shell scripts. The shell provides many of the same features as a basic procedural programming language. Let’s write some code. Type in this command: $ j=123 $ echo $j We just created a variable named j referencing the string 123. The echo command printed out the value of the variable. We had to use a dollar sign ($) when referencing the variable in another command. Next, type in: $ j=1+1 $ echo $j Is that what you expected? The shell just interprets the variable value as a string. It’s not going to do any sort of computation. Typing in shell script commands on the command line is sort of pointless. We want to be able to create scripts that we can run over-and-over. Let’s create our first shell script. Use the nano editor to create a file named myscript. When the file is open in the editor, type in the following lines of code: #!/bin/bash echo Hello $1 Now quit the editor and save your file. We can run our script by typing: $ ./myscript World Er, what happened? Permission denied. Didn’t we create this file? Why can’t we run it? We can’t run the script file because we haven’t set the execute permission on the file. Type in: $ chmod u+x myscript This modifies the file access control list to allow the owner of the file to execute it. Let’s try to run the command again. Hit the up-arrow key a couple times until the ./myscript World command is displayed and hit enter. Hooray! Our first shell script. It’s probably a bit underwhelming. No problem, we’ll make it a little more complex. The script took a single argument called World. Any arguments provided to a shell script are represented as consecutively numbered variables inside the script ($1, $2, etc). Pretty simple. You might be wondering why we had to type the ./ characters before the name of our script file. Try to type in the command without them: $ myscript World Command not found. That seems a little weird. Aren’t we currently in the directory where the shell script is located? Well, that’s just not how the shell works. When you enter a command into the shell, it looks for the command in a predefined set of directories on the server called your PATH. Since your script file isn’t in your special path, the shell reports it as not found. By typing in the ./ characters before the command name you are basically forcing the shell to look for your script in the current directory instead of the default path. Create another file called cleanup using nano. In the file editor window type: #!/bin/bash # My cleanup script mkdir archive mv file* archive Exit the editor window and save the file. Change the permissions on the script file so that you can execute it. Now run the command: $ ./cleanup Take a look at the file directory listing. Notice the archive directory? List the contents of that directory. The script automatically created a new directory and moved three files into it. Anything you can do manually at a command prompt can be automated using a shell script. Let’s create one more shell script. Use nano to create a script called namelist. Here is the content of the script: #!/bin/bash # for-loop test script names='Jason John Jane' for i in $names do echo Hello $i done Change the permissions on the script file so that you can execute it. Run the command: $ ./namelist The script will loop through a set of names stored in a variable displaying each one. Scripts support several programming constructs like for-loops, do-while loops, and if-then-else. These building blocks allow you to create fairly complex scripts for automating tasks. Installing packages and services We’re nearing the end of this assignment. But before we finish, let’s install some new software packages on our server. The first thing we should do is make sure all the current packages installed on our Linux server are up-to-date. Type in: $ sudo yum update -y This is one of those really powerful commands that requires sudo access. The system will review the currently installed packages and go out to the Internet and download appropriate updates. Next, let’s install an Apache web server on our system. Type in: $ sudo yum install httpd -y Bam! You probably never knew that installing a web server was so easy. We’re not going to actually use the web server in this exercise, but we will in future assignments. We installed the web server, but is it actually running? Let’s check. Type in: $ sudo service httpd status Nope. Let’s start it. Type: $ sudo service httpd start We can use the service command to control the services running on the system. Let’s setup the service so that it automatically starts when the system boots up. Type in: $ sudo chkconfig httpd on Cool. We installed the Apache web server on our system, but what other programs are currently running? We can use the pscommand to find out. Type in: $ ps -ax Lots of processes are running on our system. We can even look at the overall performance of our system using the topcommand. Let’s try that now. Type in: $ top The display might seem a little overwhelming at first. You should see lots of performance information displayed including the cpu usage, free memory, and a list of running tasks. We’re almost across the finish line. Let’s make sure all of our valuable work is stored in a git repository. First, we need to install git. Type in the command: $ sudo yum install git -y Check your work It’s very important to check your work before submitting it for grading. A misspelled, misplaced or missing file will cost you points. This may seem harsh, but the reality is that these sorts of mistakes have consequences in the real world. For example, a server instance could fail to launch properly and impact customers because a single required file is missing. Here is what the contents of your git repository should look like before final submission: ┣archive ┃ ┣ file1 ┃ ┣ file2 ┃ ┗ file3 ┣ namelist ┗ myfile.conf Saving our work in the git repository Next, make sure you are still in your home directory (/home/ec2-user). We will install the git repository you created at the beginning of this exercise. You will need to modify this command by typing in the GitHub repository URL you copied earlier. $ git clone <your GitHub URL here>.git Example: git clone https://github.com/UST-SEIS665/hw2-seis665-02-spring2019-<your github id>.git The git application will ask you for your GitHub username and password. Note, if you have multi-factor authentication enabled on your GitHub account you will need to provide a personal token instead of your password. Git will clone (copy) the repository from GitHub to your Linux server. Since the repository is empty the clone happens almost instantly. Check to make sure that a sub-directory called "hw2-seis665-02-spring2019-<username>" exists in the current directory (where <username> is your GitHub account name). Git automatically created this directory as part of the cloning process. Change to the hw2-seis665-02-spring2019-<username> directory and type: $ ls -la Notice the .git hidden directory? This is where git actually stores all of the file changes in your repository. Nothing is actually in your repository yet. Change back to the parent directory (cd ..). Next, let’s move some of our files into the repository. Type: $ mv archive hw2-seis665-02-spring2019-<username> $ mv namelist hw2-seis665-02-spring2019-<username> $ mv myfile.conf hw2-seis665-02-spring2019-<username> Hopefully, you remembered to use the auto-complete function to reduce some of that typing. Change to the hw2-seis665-02-spring2019-<username> directory and list the directory contents. Your files are in the working directory, but are not actually stored in the repository because they haven’t been committed yet. Type in: $ git status You should see a list of untracked files. Let’s tell git that we want these files tracked. Type in: $ git add * Now type in the git status command again. Notice how all the files are now being tracked and are ready to be committed. These files are in the git staging area. We’ll commit them to the repository next. Type: $ git commit -m 'assignment 2 files' Next, take a look at the commit log. Type: $ git log You should see your commit listed along with an assigned hash (long string of random-looking characters). Finally, let’s save the repository to our GitHub account. Type in: $ git push origin master The git client will ask you for your GitHub username and password before pushing the repository. Go back to the GitHub.com website and login if you have been logged out. Click on the repository link for the assignment. Do you see your files listed there? Congratulations, you completed the exercise! Terminate server The last step is to terminate your Linux instance. AWS will bill you for every hour the instance is running. The cost is nominal, but there’s no need to rack up unnecessary charges. Here are the steps to terminate your instance: Log into your AWS account and click on the EC2 dashboard. Click the Instances menu item. Select your server in the instances table. Click on the Actions drop down menu above the instances table. Select the Instance State menu option Click on the Terminate action. Your Linux instance will shutdown and disappear in a few minutes. The EC2 dashboard will continue to display the instance on your instance listing for another day or so. However, the state of the instance will be terminated. Submitting your assignment — IMPORTANT! If you haven’t already, please e-mail me your GitHub username in order to receive credit for this assignment. There is no need to email me to tell me that you have committed your work to GitHub or to ask me if your GitHub submission worked. If you can see your work in your GitHub repository, I can see your work.

Natural Language Inference is fundamental to many Natural Language Processing applications such as semantic search and question answering. The task of NLI has gained significant attention in the recent times due to the release of fairly large scale, challenging datasets. Present approaches that address NLI are largely focused on learning based on the given text in order to classify whether the given premise entails, contradicts, or is neutral to the given hypothesis. On the other hand, techniques for Inference, as a central topic in artificial intelligence, has had knowledge bases playing an important role, in particular for formal reasoning tasks. While, there are many open knowledge bases that comprise of various types of information, their use for natural language inference has not been well explored. In this work, we present a simple technique that can harnesses knowledge bases, provided in the form of a graph, for natural language inference.

Embeddings: State-of-the-art Text Representations for Natural Language Processing tasks, an initial version of library focus on the Polish Language

chunkipy is an extremely useful tool for segmenting long texts into smaller chunks, based on either a character or token count. With customizable chunk sizes and splitting strategies, chunkipy provides flexibility and control for various text processing tasks.

A Python-based voice assistant that processes voice commands to perform tasks like web searches, setting reminders, and answering queries. Utilizes speech recognition and text-to-speech libraries for seamless user interaction and task automation.

The system was developed with USSD or SMS technology to be used without limits on all modern or outdated mobile devices. The main objective is to reach the entire population by offering the most comfort possible without complications in technologies in terms of use and their monetary movements. More about this source text. The main operation is to buy your balance at any shipping point and use it at any time sending to anyone and keep your balance without moving so much. Because the thing goes like this: We have to have a main number that answers all the requests of the final client, consulting everything in a database and saving. The main task in the foreground is to get an automated server to receive messages from the subscribers to the system, their requests, and this server simultaneously processes the request for the message by responding to the requester, the requester at the same time confirms his transaction with a pin code According to the transaction, the commissions are charged in your wallet, in the same way there will be users as affiliates where they carry out their operations with their balances and the commissions are distributed between the same and the company according to the established percentage, this event must be registered in a database that will store the customer's information, then this, when made possible, must be a part of the Administration panel, to be able to see all the requests processed, the balances of the clients, their operations, a part to enable or create new clients and users by roles. A confirmation PIN must be sent from the end user, for security reasons, an encrypted PIN. Integrate payment gateway for international clients and they will use VISA to recharge their wallet. -> The user will use their VISA card to recharge their balance if it is what they have and we will have to use a gateway, NOW, nationwide, the use of cards is almost 0%, the second option for natives is: We have to add the option to create ticket and printed or small printed cards to scratch that will contain a code, for example: 1286565XXX, then once scratch and enter it, a balance is recharged, then they will have to be GENERATED with the same More about this source text. system, maintaining referential integrity and printing them. -> Okay, will you buy me scratch cards and give me cash? YES. -> Perfect, in some kiosks installed for example in the streets and commercial places. A well-organized project makes maintenance easy. Error correction. Remember business logic well. There must be a part to configure or parameterize the commissions according to the amounts to be sent. Each user must have their balance account and commissions account, these commissions must be withdrawn at any time and be transferred to their account of movements. If the user asks for a history of their transactions, it is sent to them at the same time as an Excel or PDF file. BUSINESS LOGIC: • Prices of cards to print: 10,000, 25,000, 60,000, 90,000, 125,000, 300,000. • Make the shipment the interest commission is 20% • Receive by saving in the wallet the commission is 20% interest, it is entered into your account • Receive by taking cash the commission of 20% is transferred to the effective payer. • Make payment of a bill for a service with your wallet the standard spending commission is 1,000 • Receive payment of an invoice for a paid service the standard expense commission is 1,000 • Make payment of an article or product the expense commission is 5%. • Receive payment for an item or product, the expense commission is 5%. • Buy GETESA or MUNI balance, the expense commission is 50XAF. CASES: CASE 0: REGISTER: TYPES OF USERS: SUPER_ADMIN, ADMIN, FRANCHISE_CLIETE, NORMAL_CLIENT • Send word: HELLO, respond with an image incorporated wallet + Template; CORPORATED WALLET Greetings. Your shipments, purchases earnings and wallet "You win and I win" Send: R -> Register S -> If you are already registered IF -> More information (Yes, it is the first time). FAMILY (if already registered) A. Reload. • Receive menu descriptions of services: A. Register, B. Send, C. Receive, D. Join to win, E. My balance, F. Extract, G. About us. More about CASES. • Register ok: Credit card code (mandatory), ^ Telephone number (obviously already obtained with the sms), Full name, City, PIN code, Recharge code • Verify account. CASE 1: PERFORM OPERATION: • Send word: FAMILY • Receive menu descriptions of services: AB. Recharge. B. Send, B1. Send payment for a service, C. Receive, C1. Receive service payment. D. Join to win, E. My balance, FA. Pay bills, FB. Pagar luz, F. Extract, G. About us. • Reload: Put scratch card code (purchased at any kiosk or agency) • Receive sms balance. • REFILL WITH VISA CARD: link from stripe or any payment website with OTP • Synchronize the balance of the currency or reloaded currency CASE 2: SEND: • Amount to send • Recipient phone • Balance ok? • Ask for confirmation PIN • Debit sender customer account: amount sent, amount on commission (percentage setting) • Distribute or distribute commissions: company percentage to company commissions account, sender percentage to commissions account. • Complete operation message: Sender, amount, commission, remaining balance, date CASE 3: RECEIVE: Code shipping • Sender • Amount • PIN confirmation • Operation message CASE 4: JOIN TO WIN • Send word: WIN • Request card or recharge code (credit account with higher balance) • Transform to account (FRANQUICIA_CLIETE) • Automatically establish commission percentage for sending or receiving. (SUPER ADMIN PANEL } • Ok: account info message. CASE 5: ACCOUNT INFORMATION • Send word: BALANCE or INFO • Info message: Name, balance, commissions CASE 6: WITHDRAWAL COMMISSIONS • Send keyword: DAME • Amount to withdraw • PIN confirmation • Debit commissions account • Top up main customer account. • Regularize account of commissions. • Status information. CASE 7: CHANGE PIN • Send PIN word • Change? • old PIN • New PIN • new PIN confirmation • PIN message changed successfully CASE 8 FB: PAY LIGHT • SEGESA phone • Counter code • Amount payable • PIN confirmation • Invoice in PDF • Successful payment • Debit 1000 • Automatic collection of the amount of 1000 SEGESA account • Income of the amount paid to the SEGESA account • Ge CASE 9 F: REQUEST EXTRACT • Write word: EX • Dates: Start date, End date, ALL • Excel file with transaction information. CASE 10 G: ABOUT US • Send word: CONTACT • Detailed information on the company's services and contacts. CASE 11: ADMINISTRATIVE PANEL • Statistics of operations and statuses of Chart.js accounts • Admin users • Manage clients • Receive • Send • Operations • Returns • Payments • Links • Accounts • Setting • Generate balances or scratch cards WALLET OPERATIONS. CASE 0-OB: RECEIVE PAYMENT OF A SERVICE. • Keyword: PS C1 • Ask to put amount • Ask to put a pay phone • Ask to put a description • Receive descriptive sms and send payment code automatically • Receive authorized payer code • Confirm transaction code • Apply expense commission CASE 1-OB: Make payment for a service • Receive payment code from provider • Keyword: B1 • Enter code • See payment info. • Q-> Confirm • PIN confirmation • Debit the payer account the amount • Debt account the payer commission expenses • Change transaction status. Beforehand in the future I want to consume a transaction by its code in another application and verify its effectiveness in the future with another application that I have in my fan of projects. It will be a big platform, MY VISION.

MiroEval: A benchmark and evaluation framework for deep research agents — 100 tasks (70 text, 30 multimodal) assessed across synthesis quality, factuality, and research process. 13 systems evaluated.

Text processing library for sentiment analysis and related tasks

Gear61 / Random-Number-Generator Code Issues 5 Pull requests 0 Projects 0 Wiki Pulse projectFilesBackup/.idea/workspace.xml <?xml version="1.0" encoding="UTF-8"?> <project version="4"> <component name="AndroidLayouts"> <shared> <config /> </shared> </component> <component name="AndroidLogFilters"> <option name="TOOL_WINDOW_CONFIGURED_FILTER" value="Show only selected application" /> </component> <component name="ChangeListManager"> <list default="true" id="f5e37520-ca17-4d94-bb6c-b4cbc9c73568" name="Default" comment="" /> <ignored path="rngplus.iws" /> <ignored path=".idea/workspace.xml" /> <option name="EXCLUDED_CONVERTED_TO_IGNORED" value="true" /> <option name="TRACKING_ENABLED" value="true" /> <option name="SHOW_DIALOG" value="false" /> <option name="HIGHLIGHT_CONFLICTS" value="true" /> <option name="HIGHLIGHT_NON_ACTIVE_CHANGELIST" value="false" /> <option name="LAST_RESOLUTION" value="IGNORE" /> </component> <component name="ChangesViewManager" flattened_view="true" 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value="$PROJECT_DIR$" /> <option name="name" value="deviceCheck" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="generateDebugAndroidTestAssets" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="generateDebugAndroidTestBuildConfig" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="generateDebugAndroidTestResValues" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="generateDebugAndroidTestResources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="generateDebugAndroidTestSources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="generateDebugAssets" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="generateDebugBuildConfig" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="generateDebugResValues" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="generateDebugResources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="generateDebugSources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="generateReleaseAssets" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="generateReleaseBuildConfig" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="generateReleaseResValues" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="generateReleaseResources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="generateReleaseSources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="incrementalDebugAndroidTestJavaCompilationSafeguard" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="incrementalDebugJavaCompilationSafeguard" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="incrementalDebugUnitTestJavaCompilationSafeguard" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="incrementalReleaseJavaCompilationSafeguard" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="incrementalReleaseUnitTestJavaCompilationSafeguard" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Installs the Debug build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="installDebug" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Installs the android (on device) tests for the Debug build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="installDebugAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="jarDebugClasses" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="jarReleaseClasses" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Runs lint on all variants." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="lint" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Runs lint on the Debug build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="lintDebug" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Runs lint on the Release build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="lintRelease" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Runs lint on just the fatal issues in the Release build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="lintVitalRelease" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="mergeDebugAndroidTestAssets" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="mergeDebugAndroidTestJniLibFolders" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="mergeDebugAndroidTestResources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="mergeDebugAndroidTestShaders" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="mergeDebugAssets" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="mergeDebugJniLibFolders" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="mergeDebugResources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="mergeDebugShaders" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="mergeReleaseAssets" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="mergeReleaseJniLibFolders" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="mergeReleaseResources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="mergeReleaseShaders" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Creates a version of android.jar that's suitable for unit tests." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="mockableAndroidJar" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="packageDebug" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="packageDebugAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="packageRelease" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="preBuild" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="preDebugAndroidTestBuild" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="preDebugBuild" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="preDebugUnitTestBuild" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prePackageMarkerForDebug" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prePackageMarkerForDebugAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prePackageMarkerForRelease" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="preReleaseBuild" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="preReleaseUnitTestBuild" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.android.support:animated-vector-drawable:23.3.0" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prepareComAndroidSupportAnimatedVectorDrawable2330Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.android.support:appcompat-v7:23.3.0" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prepareComAndroidSupportAppcompatV72330Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.android.support:cardview-v7:23.1.1" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prepareComAndroidSupportCardviewV72311Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.android.support:design:23.3.0" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prepareComAndroidSupportDesign2330Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.android.support:recyclerview-v7:23.3.0" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prepareComAndroidSupportRecyclerviewV72330Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.android.support:support-v4:23.3.0" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prepareComAndroidSupportSupportV42330Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.android.support:support-vector-drawable:23.3.0" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prepareComAndroidSupportSupportVectorDrawable2330Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.github.afollestad.material-dialogs:core:0.8.5.8" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prepareComGithubAfollestadMaterialDialogsCore0858Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.github.rey5137:material:1.2.2" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prepareComGithubRey5137Material122Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.joanzapata.iconify:android-iconify:2.2.2" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prepareComJoanzapataIconifyAndroidIconify222Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.joanzapata.iconify:android-iconify-fontawesome:2.2.2" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prepareComJoanzapataIconifyAndroidIconifyFontawesome222Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.joanzapata.iconify:android-iconify-ionicons:2.2.2" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prepareComJoanzapataIconifyAndroidIconifyIonicons222Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prepareDebugAndroidTestDependencies" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prepareDebugDependencies" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prepareDebugUnitTestDependencies" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare me.zhanghai.android.materialprogressbar:library:1.1.5" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prepareMeZhanghaiAndroidMaterialprogressbarLibrary115Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prepareReleaseDependencies" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="prepareReleaseUnitTestDependencies" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="processDebugAndroidTestJavaRes" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="processDebugAndroidTestManifest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="processDebugAndroidTestResources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="processDebugJavaRes" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="processDebugManifest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="processDebugResources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="processDebugUnitTestJavaRes" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="processReleaseJavaRes" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="processReleaseManifest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="processReleaseResources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="processReleaseUnitTestJavaRes" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Displays the signing info for each variant." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="signingReport" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prints out all the source sets defined in this project." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="sourceSets" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Run unit tests for all variants." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="test" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Run unit tests for the debug build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="testDebugUnitTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Run unit tests for the release build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="testReleaseUnitTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="transformClassesWithDexForDebug" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="transformClassesWithDexForDebugAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="transformClassesWithDexForRelease" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="transformNative_libsWithMergeJniLibsForDebug" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="transformNative_libsWithMergeJniLibsForDebugAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="transformNative_libsWithMergeJniLibsForRelease" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="transformResourcesWithMergeJavaResForDebug" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="transformResourcesWithMergeJavaResForDebugAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="transformResourcesWithMergeJavaResForDebugUnitTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="transformResourcesWithMergeJavaResForRelease" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="transformResourcesWithMergeJavaResForReleaseUnitTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Uninstall all applications." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="uninstallAll" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Uninstalls the Debug build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="uninstallDebug" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Uninstalls the android (on device) tests for the Debug build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="uninstallDebugAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Uninstalls the Release build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="uninstallRelease" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="validateDebugSigning" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$" /> <option name="name" value="zipalignDebug" /> </ExternalTaskPojo> </list> </value> </entry> <entry key="$PROJECT_DIR$/app"> <value> <list> <ExternalTaskPojo> <option name="description" value="Displays the Android dependencies of the project." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="androidDependencies" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Assembles all variants of all applications and secondary packages." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="assemble" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Assembles all the Test applications." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="assembleAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Assembles all Debug builds." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="assembleDebug" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="assembleDebugAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="assembleDebugUnitTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Assembles all Release builds." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="assembleRelease" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="assembleReleaseUnitTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Assembles and tests this project." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="build" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Assembles and tests this project and all projects that depend on it." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="buildDependents" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Displays all buildscript dependencies declared in project ':app'." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="buildEnvironment" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Assembles and tests this project and all projects it depends on." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="buildNeeded" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Runs all checks." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="check" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="checkDebugManifest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="checkReleaseManifest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Deletes the build directory." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="clean" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileDebugAidl" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileDebugAndroidTestAidl" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileDebugAndroidTestJavaWithJavac" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileDebugAndroidTestNdk" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileDebugAndroidTestRenderscript" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileDebugAndroidTestShaders" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileDebugAndroidTestSources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileDebugJavaWithJavac" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileDebugNdk" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileDebugRenderscript" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileDebugShaders" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileDebugSources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileDebugUnitTestJavaWithJavac" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileDebugUnitTestSources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileLint" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileReleaseAidl" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileReleaseJavaWithJavac" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileReleaseNdk" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileReleaseRenderscript" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileReleaseShaders" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileReleaseSources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileReleaseUnitTestJavaWithJavac" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="compileReleaseUnitTestSources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Displays the components produced by project ':app'. [incubating]" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="components" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Installs and runs instrumentation tests for all flavors on connected devices." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="connectedAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Runs all device checks on currently connected devices." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="connectedCheck" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Installs and runs the tests for debug on connected devices." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="connectedDebugAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Displays all dependencies declared in project ':app'." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="dependencies" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Displays the insight into a specific dependency in project ':app'." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="dependencyInsight" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Installs and runs instrumentation tests using all Device Providers." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="deviceAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Runs all device checks using Device Providers and Test Servers." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="deviceCheck" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="generateDebugAndroidTestAssets" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="generateDebugAndroidTestBuildConfig" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="generateDebugAndroidTestResValues" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="generateDebugAndroidTestResources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="generateDebugAndroidTestSources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="generateDebugAssets" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="generateDebugBuildConfig" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="generateDebugResValues" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="generateDebugResources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="generateDebugSources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="generateReleaseAssets" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="generateReleaseBuildConfig" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="generateReleaseResValues" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="generateReleaseResources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="generateReleaseSources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Displays a help message." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="help" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="incrementalDebugAndroidTestJavaCompilationSafeguard" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="incrementalDebugJavaCompilationSafeguard" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="incrementalDebugUnitTestJavaCompilationSafeguard" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="incrementalReleaseJavaCompilationSafeguard" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="incrementalReleaseUnitTestJavaCompilationSafeguard" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Installs the Debug build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="installDebug" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Installs the android (on device) tests for the Debug build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="installDebugAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="jarDebugClasses" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="jarReleaseClasses" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Runs lint on all variants." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="lint" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Runs lint on the Debug build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="lintDebug" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Runs lint on the Release build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="lintRelease" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Runs lint on just the fatal issues in the Release build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="lintVitalRelease" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="mergeDebugAndroidTestAssets" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="mergeDebugAndroidTestJniLibFolders" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="mergeDebugAndroidTestResources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="mergeDebugAndroidTestShaders" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="mergeDebugAssets" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="mergeDebugJniLibFolders" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="mergeDebugResources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="mergeDebugShaders" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="mergeReleaseAssets" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="mergeReleaseJniLibFolders" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="mergeReleaseResources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="mergeReleaseShaders" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Creates a version of android.jar that's suitable for unit tests." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="mockableAndroidJar" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Displays the configuration model of project ':app'. [incubating]" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="model" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="packageDebug" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="packageDebugAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="packageRelease" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="preBuild" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="preDebugAndroidTestBuild" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="preDebugBuild" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="preDebugUnitTestBuild" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prePackageMarkerForDebug" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prePackageMarkerForDebugAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prePackageMarkerForRelease" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="preReleaseBuild" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="preReleaseUnitTestBuild" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.android.support:animated-vector-drawable:23.3.0" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prepareComAndroidSupportAnimatedVectorDrawable2330Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.android.support:appcompat-v7:23.3.0" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prepareComAndroidSupportAppcompatV72330Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.android.support:cardview-v7:23.1.1" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prepareComAndroidSupportCardviewV72311Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.android.support:design:23.3.0" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prepareComAndroidSupportDesign2330Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.android.support:recyclerview-v7:23.3.0" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prepareComAndroidSupportRecyclerviewV72330Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.android.support:support-v4:23.3.0" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prepareComAndroidSupportSupportV42330Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.android.support:support-vector-drawable:23.3.0" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prepareComAndroidSupportSupportVectorDrawable2330Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.github.afollestad.material-dialogs:core:0.8.5.8" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prepareComGithubAfollestadMaterialDialogsCore0858Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.github.rey5137:material:1.2.2" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prepareComGithubRey5137Material122Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.joanzapata.iconify:android-iconify:2.2.2" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prepareComJoanzapataIconifyAndroidIconify222Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.joanzapata.iconify:android-iconify-fontawesome:2.2.2" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prepareComJoanzapataIconifyAndroidIconifyFontawesome222Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare com.joanzapata.iconify:android-iconify-ionicons:2.2.2" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prepareComJoanzapataIconifyAndroidIconifyIonicons222Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prepareDebugAndroidTestDependencies" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prepareDebugDependencies" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prepareDebugUnitTestDependencies" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prepare me.zhanghai.android.materialprogressbar:library:1.1.5" /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prepareMeZhanghaiAndroidMaterialprogressbarLibrary115Library" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prepareReleaseDependencies" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="prepareReleaseUnitTestDependencies" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="processDebugAndroidTestJavaRes" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="processDebugAndroidTestManifest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="processDebugAndroidTestResources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="processDebugJavaRes" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="processDebugManifest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="processDebugResources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="processDebugUnitTestJavaRes" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="processReleaseJavaRes" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="processReleaseManifest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="processReleaseResources" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="processReleaseUnitTestJavaRes" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Displays the sub-projects of project ':app'." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="projects" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Displays the properties of project ':app'." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="properties" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Displays the signing info for each variant." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="signingReport" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Prints out all the source sets defined in this project." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="sourceSets" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Displays the tasks runnable from project ':app'." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="tasks" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Run unit tests for all variants." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="test" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Run unit tests for the debug build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="testDebugUnitTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Run unit tests for the release build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="testReleaseUnitTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="transformClassesWithDexForDebug" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="transformClassesWithDexForDebugAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="transformClassesWithDexForRelease" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="transformNative_libsWithMergeJniLibsForDebug" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="transformNative_libsWithMergeJniLibsForDebugAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="transformNative_libsWithMergeJniLibsForRelease" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="transformResourcesWithMergeJavaResForDebug" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="transformResourcesWithMergeJavaResForDebugAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="transformResourcesWithMergeJavaResForDebugUnitTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="transformResourcesWithMergeJavaResForRelease" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="transformResourcesWithMergeJavaResForReleaseUnitTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Uninstall all applications." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="uninstallAll" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Uninstalls the Debug build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="uninstallDebug" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Uninstalls the android (on device) tests for the Debug build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="uninstallDebugAndroidTest" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="description" value="Uninstalls the Release build." /> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="uninstallRelease" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="validateDebugSigning" /> </ExternalTaskPojo> <ExternalTaskPojo> <option name="linkedExternalProjectPath" value="$PROJECT_DIR$/app" /> <option name="name" value="zipalignDebug" /> </ExternalTaskPojo> </list> </value> </entry> </map> </option> <option name="modificationStamps"> <map> <entry key="$PROJECT_DIR$" value="4377878861000" /> </map> </option> <option name="projectBuildClasspath"> <map> <entry key="$PROJECT_DIR$"> <value> <ExternalProjectBuildClasspathPojo> <option name="modulesBuildClasspath"> <map> <entry key="$PROJECT_DIR$"> <value> <ExternalModuleBuildClasspathPojo> <option name="entries"> <list> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/com/android/tools/build/gradle/2.1.0/gradle-2.1.0.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/com/android/tools/build/gradle-core/2.1.0/gradle-core-2.1.0.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/org/jacoco/org.jacoco.core/0.7.4.201502262128/org.jacoco.core-0.7.4.201502262128-sources.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/org/jacoco/org.jacoco.core/0.7.4.201502262128/org.jacoco.core-0.7.4.201502262128.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/org/ow2/asm/asm-commons/5.0.3/asm-commons-5.0.3-sources.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/org/ow2/asm/asm-commons/5.0.3/asm-commons-5.0.3.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/com/android/tools/build/gradle-api/2.1.0/gradle-api-2.1.0.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/com/android/tools/lint/lint/25.1.0/lint-25.1.0.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/com/android/databinding/compilerCommon/2.1.0/compilerCommon-2.1.0.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/org/ow2/asm/asm/5.0.3/asm-5.0.3-sources.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/org/ow2/asm/asm/5.0.3/asm-5.0.3.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/net/sf/proguard/proguard-gradle/5.2.1/proguard-gradle-5.2.1-sources.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/net/sf/proguard/proguard-gradle/5.2.1/proguard-gradle-5.2.1.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/com/android/tools/build/transform-api/2.0.0-deprecated-use-gradle-api/transform-api-2.0.0-deprecated-use-gradle-api.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/com/android/tools/build/builder/2.1.0/builder-2.1.0.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/org/ow2/asm/asm-debug-all/5.0.1/asm-debug-all-5.0.1-sources.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/org/ow2/asm/asm-debug-all/5.0.1/asm-debug-all-5.0.1.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/org/ow2/asm/asm-tree/5.0.3/asm-tree-5.0.3-sources.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/org/ow2/asm/asm-tree/5.0.3/asm-tree-5.0.3.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/com/google/guava/guava/17.0/guava-17.0-sources.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/com/google/guava/guava/17.0/guava-17.0.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/com/android/tools/annotations/25.1.0/annotations-25.1.0.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/com/android/tools/lint/lint-checks/25.1.0/lint-checks-25.1.0.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/org/eclipse/jdt/core/compiler/ecj/4.4.2/ecj-4.4.2-sources.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/org/eclipse/jdt/core/compiler/ecj/4.4.2/ecj-4.4.2.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/com/googlecode/juniversalchardet/juniversalchardet/1.0.3/juniversalchardet-1.0.3.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/com/tunnelvisionlabs/antlr4/4.5/antlr4-4.5.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/commons-io/commons-io/2.4/commons-io-2.4-sources.jar" /> <option value="$APPLICATION_HOME_DIR$/gradle/m2repository/commons-io/commons-io/2.4/commons-io-2.4.jar" /> <option 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</state> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/java/com/randomappsinc/randomnumbergeneratorplus/Persistence/Database/RNGConfiguration.java"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="-0.34920636"> <caret line="17" column="30" selection-start-line="17" selection-start-column="30" selection-end-line="17" selection-end-column="30" /> </state> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/res/values/edit_excluded_strings.xml"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="0.63559324"> <caret line="15" column="74" selection-start-line="15" selection-start-column="74" selection-end-line="15" selection-end-column="74" /> <folding /> </state> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/java/com/randomappsinc/randomnumbergeneratorplus/Utils/RandUtils.java"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="0.0"> <caret line="166" column="0" selection-start-line="166" selection-start-column="0" selection-end-line="166" selection-end-column="0" /> </state> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/java/com/randomappsinc/randomnumbergeneratorplus/Activities/EditConfigurationsActivity.java"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="0.7010582"> <caret line="27" column="76" selection-start-line="27" selection-start-column="76" selection-end-line="27" selection-end-column="76" /> </state> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/java/com/randomappsinc/randomnumbergeneratorplus/Activities/EditExcludedActivity.java"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="-1.2222222"> <caret line="37" column="24" selection-start-line="37" selection-start-column="24" selection-end-line="37" selection-end-column="24" /> </state> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/res/values/config_strings.xml"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="-1.875"> <caret line="3" column="46" selection-start-line="3" selection-start-column="46" selection-end-line="3" selection-end-column="46" /> <folding /> </state> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/res/values/strings.xml"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="0.0"> <caret line="33" column="36" selection-start-line="33" selection-start-column="36" selection-end-line="33" selection-end-column="36" /> <folding /> </state> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/java/com/randomappsinc/randomnumbergeneratorplus/Utils/MyApplication.java"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="0.0"> <caret line="22" column="16" selection-start-line="22" selection-start-column="16" selection-end-line="22" selection-end-column="16" /> </state> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/build.gradle"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="0.0"> <caret line="11" column="26" selection-start-line="11" selection-start-column="26" selection-end-line="11" selection-end-column="26" /> </state> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/res/layout/settings_item_cell.xml"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="0.0"> <caret line="10" column="32" selection-start-line="0" selection-start-column="0" selection-end-line="26" selection-end-column="15" /> <folding /> </state> </provider> <provider editor-type-id="android-designer"> <state /> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/java/com/randomappsinc/randomnumbergeneratorplus/Activities/SettingsActivity.java"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="0.0"> <caret line="21" column="4" selection-start-line="21" selection-start-column="4" selection-end-line="69" selection-end-column="5" /> <folding> <element signature="imports" expanded="false" /> </folding> </state> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/res/values/settings_strings.xml"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="0.0"> <caret line="20" column="50" selection-start-line="20" selection-start-column="50" selection-end-line="20" selection-end-column="50" /> <folding /> </state> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/res/values/styles.xml"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="0.0"> <caret line="7" column="4" selection-start-line="7" selection-start-column="4" selection-end-line="21" selection-end-column="12" /> <folding /> </state> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/res/drawable/ripple_button.xml"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="0.0"> <caret line="5" column="11" selection-start-line="5" selection-start-column="11" selection-end-line="5" selection-end-column="11" /> <folding /> </state> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/res/layout/homepage.xml"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="-0.28301886"> <caret line="1" column="48" selection-start-line="1" selection-start-column="48" selection-end-line="1" selection-end-column="48" /> <folding /> </state> </provider> <provider editor-type-id="android-designer"> <state /> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/res/layout/settings.xml"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="0.0"> <caret line="6" column="41" selection-start-line="0" selection-start-column="0" selection-end-line="14" selection-end-column="0" /> <folding /> </state> </provider> <provider editor-type-id="android-designer"> <state /> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/java/com/randomappsinc/randomnumbergeneratorplus/Activities/MainActivity.java"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="0.0"> <caret line="331" column="5" selection-start-line="296" selection-start-column="4" selection-end-line="331" selection-end-column="5" /> <folding> <element signature="imports" expanded="false" /> <element signature="e#5173#5174#0" expanded="false" /> <element signature="e#5212#5213#0" expanded="false" /> <element signature="e#5339#5340#0" expanded="false" /> <element signature="e#5378#5379#0" expanded="false" /> </folding> </state> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/res/menu/menu_main.xml"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="0.0"> <caret line="13" column="0" selection-start-line="13" selection-start-column="0" selection-end-line="13" selection-end-column="0" /> <folding /> </state> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/AndroidManifest.xml"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="-8.75"> <caret line="14" column="49" selection-start-line="14" selection-start-column="0" selection-end-line="15" selection-end-column="0" /> <folding /> </state> </provider> </entry> <entry file="file://$PROJECT_DIR$/app/src/main/res/drawable/edittext_border.xml"> <provider selected="true" editor-type-id="text-editor"> <state vertical-scroll-proportion="0.2112676"> <caret line="5" column="8" selection-start-line="0" selection-start-column="0" selection-end-line="5" selection-end-column="8" /> <folding /> </state> </provider> </entry> </component> </project> Sign out

A curated list of awesome frameworks, libraries, tools, datasets, tutorials, and research papers for Natural Language Processing (NLP). This list covers a variety of NLP tasks, from text processing and tokenization to state-of-the-art language models and applications like sentiment analysis and machine translation.

Identify the software project, create business case, arrive at a problem statement. REQUIREMENT: Window XP, Internet, MS Office, etc. Problem Description: - 1. Introduction of AI and Machine Learning: - Artificial Intelligence applies machine learning, deep learning and other techniques to solve actual problems. Artificial intelligence (AI) brings the genuine human-to-machine interaction. Simply, Machine Learning is the algorithm that give computers the ability to learn from data and then make decisions and predictions, AI refers to idea where machines can execute tasks smartly. It is a faster process in learning the risk factors, and profitable opportunities. They have a feature of learning from their mistakes and experiences. When Machine learning is combined with Artificial Intelligence, it can be a large field to gather an immense amount of information and then rectify the errors and learn from further experiences, developing in a smarter, faster and accuracy handling technique. The main difference between Machine Learning and Artificial Intelligence is , If it is written in python then it is probably machine learning, If it is written in power point then it is artificial intelligence. As there are many existing projects that are implemented using AI and Machine Learning , And one of the project i.e., Bitcoin Price Prediction :- Bitcoin (₿ ) (founder - Satoshi Nakamoto , Ledger start: 3 January 2009 ) is a digital currency, a type of electronic money. It is decentralized advanced cash without a national bank or single chairman that can be sent from client to client on the shared Bitcoin arrange without middle people's requirement. Machine learning models can likely give us the insight we need to learn about the future of Cryptocurrency. It will not tell us the future but it might tell us the general trend and direction to expect the prices to move. These machine learning models predict the future of Bitcoin by coding them out in Python. Machine learning and AI-assisted trading have attracted growing interest for the past few years. this approach is to test the hypothesis that the inefficiency of the cryptocurrency market can be exploited to generate abnormal profits. the application of machine learning algorithms to the cryptocurrency market has been limited so far to the analysis of Bitcoin prices, using random forests , Bayesian neural network , long short-term memory neural network , and other algorithms. 2. Applications/Scope of AI and Machine Learning :- a) Sentiment Analysis :- It is the classification of subjective opinions or emotions (positive, negative, and neutral) within text data using natural language processing. b) It is Characterized as a use of computerized reasoning where accessible data is utilized through calculations to process or help the handling of factual information. BITCOIN PRICE PREDICTION USING AI AND MACHINE LEARNING: - The main aim of this is to find the actual Bitcoin price in US dollars can be predicted. The chance to make a model equipped for anticipating digital currencies fundamentally Bitcoin. # It works the prediction by taking the coinMarkup cap. # CoinMarketCap provides with historical data for Bitcoin price changes, keep a record of all the transactions by recording the amount of coins in circulation and the volume of coins traded in the last 24-hours. # Quandl is used to filter the dataset by using the MAT Lab properties. 3. Problem statement: - Some AI and Machine Learning problem statements are: - a) Data Privacy and Security: Once a company has dug up the data, privacy and security is eye-catching aspect that needs to be taken care of. b) Data Scarcity: The data is a very important aspect of AI, and labeled data is used to train machines to learn and make predictions. c) Data acquisition: In the process of machine learning, a large amount of data is used in the process of training and learning. d) High error susceptibility: In the process of artificial intelligence and machine learning, the high amount of data is used. Some problem statements of Bitcoin Price Prediction using AI and Machine Learning: - a) Experimental Phase Risk: It is less experimental than other counterparts. In addition, relative to traditional assets, its level can be assessed as high because this asset is not intended for conservative investors. b) Technology Risks: There is a technological risk to other cryptocurrencies in the form of the potential appearance of a more advanced cryptocurrency. Investors may simply not notice the moment when their virtual assets lose their real value. c) Price Variability: The variability of the value of cryptocurrency are the large volumes of exchange trading, the integration of Bitcoin with various companies, legislative initiatives of regulatory bodies and many other, sometimes disregarded phenomena. d) Consumer Protection: The property of the irreversibility of transactions in itself has little effect on the risks of investing in Bitcoin as an asset. e) Price Fluctuation Prediction: Since many investors care more about whether the sudden rise or fall is worth following. Bitcoin price often fluctuates by more than 10% (or even more than 30%) at some times. f) Lacks Government Regulation: Regulators in traditional financial markets are basically missing in the field of cryptocurrencies. For instance, fake news frequently affects the decisions of individual investors. g) It is difficult to use large interval data (e.g., day-level, and month-level data) . h) The change time of mining difficulties is much longer. Moreover, do not consider the news information since it is hard to determine the authenticity of a news or predict the occurrence of emergencies.

# Cmder [](https://gitter.im/cmderdev/cmder?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) [](https://ci.appveyor.com/project/MartiUK/cmder) Cmder is a **software package** created out of pure frustration over absence of usable console emulator on Windows. It is based on [ConEmu](https://conemu.github.io/) with *major* config overhaul, comes with a Monokai color scheme, amazing [clink](https://chrisant996.github.io/clink/) (further enhanced by [clink-completions](https://github.com/vladimir-kotikov/clink-completions)) and a custom prompt layout.  ## Why use it The main advantage of Cmder is portability. It is designed to be totally self-contained with no external dependencies, which makes it great for **USB Sticks** or **cloud storage**. So you can carry your console, aliases and binaries (like wget, curl and git) with you anywhere. The Cmder's user interface is also designed to be more eye pleasing, and you can compare the main differences between Cmder and ConEmu [here](https://conemu.github.io/en/cmder.html). ## Installation ### Single User Portable Config 1. Download the [latest release](https://github.com/cmderdev/cmder/releases/) 2. Extract the archive. *Note: This path should not be `C:\Program Files` or anywhere else that would require Administrator access for modifying configuration files* 3. (optional) Place your own executable files into the `%cmder_root%\bin` folder to be injected into your PATH. 4. Run `Cmder.exe` ### Shared Cmder install with Non-Portable Individual User Config 1. Download the [latest release](https://github.com/cmderdev/cmder/releases/) 2. Extract the archive to a shared location. 3. (optional) Place your own executable files and custom app folders into the `%cmder_root%\bin`. See: [bin/README.md](./bin/Readme.md) - This folder to be injected into your PATH by default. - See `/max_depth [1-5]` in 'Command Line Arguments for `init.bat`' table to add subdirectories recursively. 4. (optional) Place your own custom app folders into the `%cmder_root%\opt`. See: [opt/README.md](./opt/Readme.md) - This folder will NOT be injected into your PATH so you have total control of what gets added. 5. Run `Cmder.exe` with `/C` command line argument. Example: `cmder.exe /C %userprofile%\cmder_config` * This will create the following directory structure if it is missing. ``` c:\users\[CH JaDi Rajput]\cmder_config ├───bin ├───config │ └───profile.d └───opt ``` - (optional) Place your own executable files and custom app folders into `%userprofile%\cmder_config\bin`. - This folder to be injected into your PATH by default. - See `/max_depth [1-5]` in 'Command Line Arguments for `init.bat`' table to add subdirectories recursively. - (optional) Place your own custom app folders into the `%user_profile%\cmder_config\opt`. - This folder will NOT be injected into your PATH so you have total control of what gets added. * Both the shared install and the individual user config locations can contain a full set of init and profile.d scripts enabling shared config with user overrides. See below. ## Cmder.exe Command Line Arguments | Argument | Description | | ------------------- | ----------------------------------------------------------------------- | | `/C [user_root_path]` | Individual user Cmder root folder. Example: `%userprofile%\cmder_config` | | `/M` | Use `conemu-%computername%.xml` for ConEmu settings storage instead of `user_conemu.xml` | | `/REGISTER [ALL, USER]` | Register a Windows Shell Menu shortcut. | | `/UNREGISTER [ALL, USER]` | Un-register a Windows Shell Menu shortcut. | | `/SINGLE` | Start Cmder in single mode. | | `/START [start_path]` | Folder path to start in. | | `/TASK [task_name]` | Task to start after launch. | | `/X [ConEmu extras pars]` | Forwards parameters to ConEmu | ## Context Menu Integration So you've experimented with Cmder a little and want to give it a shot in a more permanent home; ### Shortcut to open Cmder in a chosen folder 1. Open a terminal as an Administrator 2. Navigate to the directory you have placed Cmder 3. Execute `.\cmder.exe /REGISTER ALL` _If you get a message "Access Denied" ensure you are executing the command in an **Administrator** prompt._ In a file explorer window right click in or on a directory to see "Cmder Here" in the context menu. ## Keyboard shortcuts ### Tab manipulation * <kbd>Ctrl</kbd> + <kbd>T</kbd> : New tab dialog (maybe you want to open cmd as admin?) * <kbd>Ctrl</kbd> + <kbd>W</kbd> : Close tab * <kbd>Ctrl</kbd> + <kbd>D</kbd> : Close tab (if pressed on empty command) * <kbd>Shift</kbd> + <kbd>Alt</kbd> + <kbd>#Number</kbd> : Fast new tab: <kbd>1</kbd> - CMD, <kbd>2</kbd> - PowerShell * <kbd>Ctrl</kbd> + <kbd>Tab</kbd> : Switch to next tab * <kbd>Ctrl</kbd> + <kbd>Shift</kbd> + <kbd>Tab</kbd> : Switch to previous tab * <kbd>Ctrl</kbd> + <kbd>#Number</kbd> : Switch to tab #Number * <kbd>Alt</kbd> + <kbd>Enter</kbd>: Fullscreen ### Shell * <kbd>Ctrl</kbd> + <kbd>Alt</kbd> + <kbd>U</kbd> : Traverse up in directory structure (lovely feature!) * <kbd>End</kbd>, <kbd>Home</kbd>, <kbd>Ctrl</kbd> : Traversing text with as usual on Windows * <kbd>Ctrl</kbd> + <kbd>R</kbd> : History search * <kbd>Shift</kbd> + Mouse : Select and copy text from buffer _(Some shortcuts are not yet documented, though they exist - please document them here)_ ## Features ### Access to multiple shells in one window using tabs You can open multiple tabs each containing one of the following shells: | Task | Shell | Description | | ---- | ----- | ----------- | | Cmder | `cmd.exe` | Windows `cmd.exe` shell enhanced with Git, Git aware prompt, Clink (GNU Readline), and Aliases. | | Cmder as Admin | `cmd.exe` | Administrative Windows `cmd.exe` Cmder shell. | | PowerShell | `powershell.exe` | Windows PowerShell enhanced with Git and Git aware prompt . | | PowerShell as Admin | `powershell.exe` | Administrative Windows `powershell.exe` Cmder shell. | | Bash | `bash.exe` | Unix/Linux like bash shell running on Windows. | | Bash as Admin | `bash.exe` | Administrative Unix/Linux like bash shell running on Windows. | | Mintty | `bash.exe` | Unix/Linux like bash shell running on Windows. See below for Mintty configuration differences | | Mintty as Admin | `bash.exe` | Administrative Unix/Linux like bash shell running on Windows. See below for Mintty configuration differences | Cmder, PowerShell, and Bash tabs all run on top of the Windows Console API and work as you might expect in Cmder with access to use ConEmu's color schemes, key bindings and other settings defined in the ConEmu Settings dialog. ⚠ *NOTE:* Only the full edition of Cmder comes with a pre-installed bash, using a vendored [git-for-windows](https://gitforwindows.org/) installation. The pre-configured Bash tabs may not work on Cmder mini edition without additional configuration. You may however, choose to use an external installation of bash, such as Microsoft's [Subsystem for Linux](https://docs.microsoft.com/en-us/windows/wsl/install-win10) (called WSL) or the [Cygwin](https://cygwin.com/) project which provides POSIX support on windows. ⚠ *NOTE:* Mintty tabs use a program called 'mintty' as the terminal emulator that is not based on the Windows Console API, rather it's rendered graphically by ConEmu. Mintty differs from the other tabs in that it supports xterm/xterm-256color TERM types, and does not work with ConEmu settings like color schemes and key bindings. As such, some differences in functionality are to be expected, such as Cmder not being able to apply a system-wide configuration to it. As a result mintty specific config is done via the `[%USERPROFILE%|$HOME]/.minttyrc` file. You may read more about Mintty and its config file [here](https://github.com/mintty/mintty). An example of setting Cmder portable terminal colors for mintty: From a bash/mintty shell: ``` cd $CMDER_ROOT/vendor git clone https://github.com/karlin/mintty-colors-solarized.git cd mintty-colors-solarized/ echo source \$CMDER_ROOT/vendor/mintty-colors-solarized/mintty-solarized-dark.sh>>$CMDER_ROOT/config/user_profile.sh ``` You may find some Monokai color schemes for mintty to match Cmder [here](https://github.com/oumu/mintty-color-schemes/blob/master/base16-monokai-mod.minttyrc). ### Changing Cmder Default `cmd.exe` Prompt Config File The default Cmder shell `cmd::Cmder` prompt is customized using `Clink` and is configured by editing a config file that exists in one of two locations: - Single User Portable Config `%CMDER_ROOT%\config\cmder_prompt_config.lua` - Shared Cmder install with Non-Portable Individual User Config `%CMDER_USER_CONFIG%\cmder_prompt_config.lua` If your Cmder setup does not have this file create it from `%CMDER_ROOT%\vendor\cmder_prompt_config.lua.default` Customizations include: - Colors. - Single/Multi-line. - Full path/Folder only. - `[user]@[host]` to the beginning of the prompt. - `~` for home directory. - `λ` symbol Documentation is in the file for each setting. ### Changing Cmder Default `cmd.exe` Shell Startup Behaviour Using Task Arguments 1. Press <kbd>Win</kbd> + <kbd>Alt</kbd> + <kbd>T</kbd> 1. Click either: * `1. {cmd::Cmder as Admin}` * `2. {cmd::Cmder}` 1. Add command line arguments where specified below: *Note: Pay attention to the quotes!* ``` cmd /s /k ""%ConEmuDir%\..\init.bat" [ADD ARGS HERE]" ``` ##### Command Line Arguments for `init.bat` | Argument | Description | Default | | ----------------------------- | ---------------------------------------------------------------------------------------------- | ------------------------------------- | | `/c [user cmder root]` | Enables user bin and config folders for 'Cmder as admin' sessions due to non-shared environment. | not set | | `/d` | Enables debug output. | not set | | `/f` | Enables Cmder Fast Init Mode. This disables some features, see pull request [#1492](https://github.com/cmderdev/cmder/pull/1942) for more details. | not set | | `/t` | Enables Cmder Timed Init Mode. This displays the time taken run init scripts | not set | | `/git_install_root [file path]` | User specified Git installation root path. | `%CMDER_ROOT%\vendor\Git-for-Windows` | | `/home [home folder]` | User specified folder path to set `%HOME%` environment variable. | `%userprofile%` | | `/max_depth [1-5]` | Define max recurse depth when adding to the path for `%cmder_root%\bin` and `%cmder_user_bin%` | 1 | | `/nix_tools [0-2]` | Define how `*nix` tools are added to the path. Prefer Windows Tools: 1, Prefer *nix Tools: 2, No `/usr/bin` in `%PATH%`: 0 | 1 | | `/svn_ssh [path to ssh.exe]` | Define `%SVN_SSH%` so we can use git svn with ssh svn repositories. | `%GIT_INSTALL_ROOT%\bin\ssh.exe` | | `/user_aliases [file path]` | File path pointing to user aliases. | `%CMDER_ROOT%\config\user_aliases.cmd` | | `/v` | Enables verbose output. | not set | | (custom arguments) | User defined arguments processed by `cexec`. Type `cexec /?` for more usage. | not set | ### Cmder Shell User Config Single user portable configuration is possible using the cmder specific shell config files. Edit the below files to add your own configuration: | Shell | Cmder Portable User Config | | ------------- | ----------------------------------------- | | Cmder | `%CMDER_ROOT%\config\user_profile.cmd` | | PowerShell | `$ENV:CMDER_ROOT\config\user_profile.ps1` | | Bash/Mintty | `$CMDER_ROOT/config/user_profile.sh` | Note: Bash and Mintty sessions will also source the `$HOME/.bashrc` file if it exists after it sources `$CMDER_ROOT/config/user_profile.sh`. You can write `*.cmd|*.bat`, `*.ps1`, and `*.sh` scripts and just drop them in the `%CMDER_ROOT%\config\profile.d` folder to add startup config to Cmder. | Shell | Cmder `Profile.d` Scripts | | ------------- | -------------------------------------------------- | | Cmder | `%CMDER_ROOT%\config\profile.d\*.bat and *.cmd` | | PowerShell | `$ENV:CMDER_ROOT\config\profile.d\*.ps1` | | Bash/Mintty | `$CMDER_ROOT/config/profile.d/*.sh` | #### Git Status Opt-Out To disable Cmder prompt git status globally add the following to `~/.gitconfig` or locally for a single repo `[repo]/.git/config` and start a new session. *Note: This configuration is not portable* ``` [cmder] status = false # Opt out of Git status for 'ALL' Cmder supported shells. cmdstatus = false # Opt out of Git status for 'Cmd.exe' shells. psstatus = false # Opt out of Git status for 'Powershell.exe and 'Pwsh.exe' shells. shstatus = false # Opt out of Git status for 'bash.exe' shells. ``` ### Aliases #### Cmder(`Cmd.exe`) Aliases You can define simple aliases for `cmd.exe` sessions with a command like `alias name=command`. Cmd.exe aliases support optional parameters through the `$1-9` or the `$*` special characters so the alias `vi=vim.exe $*` typed as `vi [filename]` will open `[filename]` in `vim.exe`. Cmd.exe aliases can also be more complex. See: [DOSKEY.EXE documentation](https://docs.microsoft.com/en-us/windows-server/administration/windows-commands/doskey) for additional details on complex aliases/macros for `cmd.exe` Aliases defined using the `alias.bat` command will automatically be saved in the `%CMDER_ROOT%\config\user_aliases.cmd` file To make an alias and/or any other profile settings permanent add it to one of the following: Note: These are loaded in this order by `$CMDER_ROOT/vendor/init.bat`. Anything stored in `%CMDER_ROOT%` will be a portable setting and will follow cmder to another machine. * `%CMDER_ROOT%\config\profile.d\*.cmd` and `\*.bat` * `%CMDER_ROOT%\config\user_aliases.cmd` * `%CMDER_ROOT%\config\user_profile.cmd` #### Bash.exe|Mintty.exe Aliases Bash shells support simple and complex aliases with optional parameters natively so they work a little different. Typing `alias name=command` will create an alias only for the current running session. To make an alias and/or any other profile settings permanent add it to one of the following: Note: These are loaded in this order by `$CMDER_ROOT/vendor/git-for-windows/etc/profile.d/cmder.sh`. Anything stored in `$CMDER_ROOT` will be a portable setting and will follow cmder to another machine. * `$CMDER_ROOT/config/profile.d/*.sh` * `$CMDER_ROOT/config/user_profile.sh` * `$HOME/.bashrc` If you add bash aliases to `$CMDER_ROOT/config/user_profile.sh` they will be portable and follow your Cmder folder if you copy it to another machine. `$HOME/.bashrc` defined aliases are not portable. #### PowerShell.exe Aliases PowerShell has native simple alias support, for example `[new-alias | set-alias] alias command`, so complex aliases with optional parameters are not supported in PowerShell sessions. Type `get-help [new-alias|set-alias] -full` for help on PowerShell aliases. To make an alias and/or any other profile settings permanent add it to one of the following: Note: These are loaded in this order by `$ENV:CMDER_ROOT\vendor\user_profile.ps1`. Anything stored in `$ENV:CMDER_ROOT` will be a portable setting and will follow cmder to another machine. * `$ENV:CMDER_ROOT\config\profile.d\*.ps1` * `$ENV:CMDER_ROOT\config\user_profile.ps1` ### SSH Agent To start the vendored SSH agent simply call `start-ssh-agent`, which is in the `vendor/git-for-windows/cmd` folder. If you want to run SSH agent on startup, include the line `@call "%GIT_INSTALL_ROOT%/cmd/start-ssh-agent.cmd"` in `%CMDER_ROOT%/config/user_profile.cmd` (usually just uncomment it). ### Vendored Git Cmder is by default shipped with a vendored Git installation. On each instance of launching Cmder, an attempt is made to locate any other user provided Git binaries. Upon finding a `git.exe` binary, Cmder further compares its version against the vendored one _by executing_ it. The vendored `git.exe` binary is _only_ used when it is more recent than the user-installed one. You may use your favorite version of Git by including its path in the `%PATH%` environment variable. Moreover, the **Mini** edition of Cmder (found on the [downloads page](https://github.com/cmderdev/cmder/releases)) excludes any vendored Git binaries. ### Using external Cygwin/Babun, MSys2, WSL, or Git for Windows SDK with Cmder. You may run bash (the default shell used on Linux, macOS and GNU/Hurd) externally on Cmder, using the following instructions: 1. Setup a new task by pressing <kbd>Win</kbd> +<kbd>Alt</kbd> + <kbd>T</kbd>. 1. Click the `+` button to add a task. 1. Name the new task in the top text box. 1. Provide task parameters, this is optional. 1. Add `cmd /c "[path_to_external_env]\bin\bash --login -i" -new_console` to the `Commands` text box. **Recommended Optional Steps:** Copy the `vendor/cmder_exinit` file to the Cygwin/Babun, MSys2, or Git for Windows SDK environments `/etc/profile.d/` folder to use portable settings in the `$CMDER_ROOT/config` folder. Note: MinGW could work if the init scripts include `profile.d` but this has not been tested. The destination file extension depends on the shell you use in that environment. For example: * bash - Copy to `/etc/profile.d/cmder_exinit.sh` * zsh - Copy to `/etc/profile.d/cmder_exinit.zsh` Uncomment and edit the below line in the script to use Cmder config even when launched from outside Cmder. ``` # CMDER_ROOT=${USERPROFILE}/cmder # This is not required if launched from Cmder. ``` ### Customizing user sessions using `init.bat` custom arguments. You can pass custom arguments to `init.bat` and use `cexec.cmd` in your `user_profile.cmd` to evaluate these arguments then execute commands based on a particular flag being detected or not. `init.bat` creates two shortcuts for using `cexec.cmd` in your profile scripts. #### `%ccall%` - Evaluates flags, runs commands if found, and returns to the calling script and continues. ``` ccall=call C:\Users\user\cmderdev\vendor\bin\cexec.cmd ``` Example: `%ccall% /startnotepad start notepad.exe` #### `%cexec%` - Evaluates flags, runs commands if found, and does not return to the calling script. ``` cexec=C:\Users\user\cmderdev\vendor\bin\cexec.cmd ``` Example: `%cexec% /startnotepad start notepad.exe` It is useful when you have multiple tasks to execute `cmder` and need it to initialize the session differently depending on the task chosen. To conditionally start `notepad.exe` when you start a specific `cmder` task: * Press <kbd>win</kbd>+<kbd>alt</kbd>+<kbd>t</kbd> * Click `+` to add a new task. * Add the below to the `Commands` block: ```batch cmd.exe /k ""%ConEmuDir%\..\init.bat" /startnotepad" ``` * Add the below to your `%cmder_root%\config\user_profile.cmd` ```batch %ccall% "/startNotepad" "start" "notepad.exe"` ``` To see detailed usage of `cexec`, type `cexec /?` in cmder. ### Integrating Cmder with [Hyper](https://github.com/zeit/hyper), [Microsoft VS Code](https://code.visualstudio.com/), and your favorite IDEs Cmder by default comes with a vendored ConEmu installation as the underlying terminal emulator, as stated [here](https://conemu.github.io/en/cmder.html). However, Cmder can in fact run in a variety of other terminal emulators, and even integrated IDEs. Assuming you have the latest version of Cmder, follow the following instructions to get Cmder working with your own terminal emulator. For instructions on how to integrate Cmder with your IDE, please read our [Wiki section](https://github.com/cmderdev/cmder/wiki#cmder-integration). ## Upgrading The process of upgrading Cmder depends on the version/build you are currently running. If you have a `[cmder_root]/config/user[-|_]conemu.xml`, you are running a newer version of Cmder, follow the below process: 1. Exit all Cmder sessions and relaunch `[cmder_root]/cmder.exe`, this backs up your existing `[cmder_root]/vendor/conemu-maximus5/conemu.xml` to `[cmder_root]/config/user[-|_]conemu.xml`. * The `[cmder_root]/config/user[-|_]conemu.xml` contains any custom settings you have made using the 'Setup Tasks' settings dialog. 2. Exit all Cmder sessions and backup any files you have manually edited under `[cmder_root]/vendor`. * Editing files under `[cmder_root]/vendor` is not recommended since you will need to re-apply these changes after any upgrade. All user customizations should go in `[cmder_root]/config` folder. 3. Delete the `[cmder_root]/vendor` folder. 4. Extract the new `cmder.zip` or `cmder_mini.zip` into `[cmder_root]/` overwriting all files when prompted. If you do not have a `[cmder_root]/config/user[-|_]conemu.xml`, you are running an older version of cmder, follow the below process: 1. Exit all Cmder sessions and backup `[cmder_root]/vendor/conemu-maximus5/conemu.xml` to `[cmder_root]/config/user[-|_]conemu.xml`. 2. Backup any files you have manually edited under `[cmder_root]/vendor`. * Editing files under `[cmder_root]/vendor` is not recommended since you will need to re-apply these changes after any upgrade. All user customizations should go in `[cmder_root]/config` folder. 3. Delete the `[cmder_root]/vendor` folder. 4. Extract the new `cmder.zip` or `cmder_mini.zip` into `[cmder_root]/` overwriting all files when prompted. ## Current development builds You can download builds of the current development branch by going to AppVeyor via the following link: [](https://ci.appveyor.com/project/MartiUK/cmder/branch/master/artifacts) ## License All software included is bundled with own license The MIT License (MIT) Copyright (c) 2016 Samuel Vasko Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

A collection of Bangla newspaper and blog crawlers. Can be used to mine bangla text data for Natural Language Processing tasks.

Text classification is a fundamental task in natural language processing (NLP), used widely for spam detection, sentiment analysis, and categorization of textual data. In this Python script, we delve into building a text classification pipeline using a Naive Bayes classifier with TF-IDF (Term Frequency-Inverse Document Frequency) features.

We will build a Flask web app that can input any long piece of information such as a blog or news article and summarize it into just five lines! Text summarization is an NLP(Natural Language Processing) task. SBERT(Sentence-BERT) has been used to achieve the same.

The Florence Tool CLI provides a command-line interface for processing images using the Florence-2 model. This tool allows users to apply various visual and text-based tasks, such as object detection, captioning, and OCR, on individual images or entire folders of images.