📊 Path to a free self-taught education in Data Science!

Repository for the second edition of 'Data Science in Education Using R' by Emily A. Bovee, Ryan A. Estrellado, Joshua M. Rosenberg, and Isabella C. Velásquez

What is Python? Executive Summary Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together. Python's simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms, and can be freely distributed. Often, programmers fall in love with Python because of the increased productivity it provides. Since there is no compilation step, the edit-test-debug cycle is incredibly fast. Debugging Python programs is easy: a bug or bad input will never cause a segmentation fault. Instead, when the interpreter discovers an error, it raises an exception. When the program doesn't catch the exception, the interpreter prints a stack trace. A source level debugger allows inspection of local and global variables, evaluation of arbitrary expressions, setting breakpoints, stepping through the code a line at a time, and so on. The debugger is written in Python itself, testifying to Python's introspective power. On the other hand, often the quickest way to debug a program is to add a few print statements to the source: the fast edit-test-debug cycle makes this simple approach very effective. What is Python? Python is a popular programming language. It was created by Guido van Rossum, and released in 1991. It is used for: web development (server-side), software development, mathematics, system scripting. What can Python do? Python can be used on a server to create web applications. Python can be used alongside software to create workflows. Python can connect to database systems. It can also read and modify files. Python can be used to handle big data and perform complex mathematics. Python can be used for rapid prototyping, or for production-ready software development. Why Python? Python works on different platforms (Windows, Mac, Linux, Raspberry Pi, etc). Python has a simple syntax similar to the English language. Python has syntax that allows developers to write programs with fewer lines than some other programming languages. Python runs on an interpreter system, meaning that code can be executed as soon as it is written. This means that prototyping can be very quick. Python can be treated in a procedural way, an object-oriented way or a functional way. Good to know The most recent major version of Python is Python 3, which we shall be using in this tutorial. However, Python 2, although not being updated with anything other than security updates, is still quite popular. In this tutorial Python will be written in a text editor. It is possible to write Python in an Integrated Development Environment, such as Thonny, Pycharm, Netbeans or Eclipse which are particularly useful when managing larger collections of Python files. Python Syntax compared to other programming languages Python was designed for readability, and has some similarities to the English language with influence from mathematics. Python uses new lines to complete a command, as opposed to other programming languages which often use semicolons or parentheses. Python relies on indentation, using whitespace, to define scope; such as the scope of loops, functions and classes. Other programming languages often use curly-brackets for this purpose. Applications for Python Python is used in many application domains. Here's a sampling. The Python Package Index lists thousands of third party modules for Python. Web and Internet Development Python offers many choices for web development: Frameworks such as Django and Pyramid. Micro-frameworks such as Flask and Bottle. Advanced content management systems such as Plone and django CMS. Python's standard library supports many Internet protocols: HTML and XML JSON E-mail processing. Support for FTP, IMAP, and other Internet protocols. Easy-to-use socket interface. And the Package Index has yet more libraries: Requests, a powerful HTTP client library. Beautiful Soup, an HTML parser that can handle all sorts of oddball HTML. Feedparser for parsing RSS/Atom feeds. Paramiko, implementing the SSH2 protocol. Twisted Python, a framework for asynchronous network programming. Scientific and Numeric Python is widely used in scientific and numeric computing: SciPy is a collection of packages for mathematics, science, and engineering. Pandas is a data analysis and modeling library. IPython is a powerful interactive shell that features easy editing and recording of a work session, and supports visualizations and parallel computing. The Software Carpentry Course teaches basic skills for scientific computing, running bootcamps and providing open-access teaching materials. Education Python is a superb language for teaching programming, both at the introductory level and in more advanced courses. Books such as How to Think Like a Computer Scientist, Python Programming: An Introduction to Computer Science, and Practical Programming. The Education Special Interest Group is a good place to discuss teaching issues. Desktop GUIs The Tk GUI library is included with most binary distributions of Python. Some toolkits that are usable on several platforms are available separately: wxWidgets Kivy, for writing multitouch applications. Qt via pyqt or pyside Platform-specific toolkits are also available: GTK+ Microsoft Foundation Classes through the win32 extensions Software Development Python is often used as a support language for software developers, for build control and management, testing, and in many other ways. SCons for build control. Buildbot and Apache Gump for automated continuous compilation and testing. Roundup or Trac for bug tracking and project management. Business Applications Python is also used to build ERP and e-commerce systems: Odoo is an all-in-one management software that offers a range of business applications that form a complete suite of enterprise management applications. Try ton is a three-tier high-level general purpose application platform.

Open Geospatial Datasets for GIS Education: This is a repository of open geospatial datasets to be used in an educational context. I created these files over years of teaching Geographic Data Science and GIS. All original datasets are freely available online with open data licenses (see the dataset attribution for details). All the datasets in this repository have been selected, cleaned, harmonised, and repackaged for GIS exercises in a higher-education context. This is a pretty time-intensive process that other educators can hopefully avoid by using these versions.

An R package associated with the Data Science in Education Using R book

Best free, open-source datasets for data science and machine learning projects. Top government data including census, economic, financial, agricultural, image datasets, labeled and unlabeled, autonomous car datasets, and much more. Data.gov NOAA - https://www.ncdc.noaa.gov/cdo-web/ atmospheric, ocean Bureau of Labor Statistics - https://www.bls.gov/data/ employment, inflation US Census Data - https://www.census.gov/data.html demographics, income, geo, time series Bureau of Economic Analysis - http://www.bea.gov/data/gdp/gross-dom... GDP, corporate profits, savings rates Federal Reserve - https://fred.stlouisfed.org/ curency, interest rates, payroll Quandl - https://www.quandl.com/ financial and economic Data.gov.uk UK Dataservice - https://www.ukdataservice.ac.uk Census data and much more WorldBank - https://datacatalog.worldbank.org census, demographics, geographic, health, income, GDP IMF - https://www.imf.org/en/Data economic, currency, finance, commodities, time series OpenData.go.ke Kenya govt data on agriculture, education, water, health, finance, … https://data.world/ Open Data for Africa - http://dataportal.opendataforafrica.org/ agriculture, energy, environment, industry, … Kaggle - https://www.kaggle.com/datasets A huge variety of different datasets Amazon Reviews - https://snap.stanford.edu/data/web-Am... 35M product reviews from 6.6M users GroupLens - https://grouplens.org/datasets/moviel... 20M movie ratings Yelp Reviews - https://www.yelp.com/dataset 6.7M reviews, pictures, businesses IMDB Reviews - http://ai.stanford.edu/~amaas/data/se... 25k Movie reviews Twitter Sentiment 140 - http://help.sentiment140.com/for-stud... 160k Tweets Airbnb - http://insideairbnb.com/get-the-data.... A TON of data by geo UCI ML Datasets - http://mlr.cs.umass.edu/ml/ iris, wine, abalone, heart disease, poker hands, …. Enron Email dataset - http://www.cs.cmu.edu/~enron/ 500k emails from 150 people From 2001 energy scandal. See the movie: The Smartest Guys in the Room. Spambase - https://archive.ics.uci.edu/ml/datase... Emails Jeopardy Questions - https://www.reddit.com/r/datasets/com... 200k Questions and answers in json Gutenberg Ebooks - http://www.gutenberg.org/wiki/Gutenbe... Large collection of books

A curated list of free courses from reputable universities that meet the requirements of an undergraduate curriculum in Data Science, excluding general education. With projects, supporting materials in an organized structure.

This repository provides a comprehensive education in health informatics, information systems, data science and analytics.

Repository of code examples for the book "Data Science First: Using Language Models in AI-Enabled Applications" -- Broken down into case studies using data from media, education, telecommunications and investment research.

Publicly available Jupyter Notebooks from ICOS Carbon Portal. Showcase access to ICOS data and how to use the data in science, education.

Path to free self-taught education in Data Science!

The Common Education Data Standards (CEDS) Data Warehouse Parquet (DW Parquet) standard is designed for data engineering and data science needs in the cloud. The DW Parquet Models mirror the SQL-based CEDS Data Warehouse. Parquet files are designed for rapid and distributed reporting across multiple technology stacks, data processing and BI tools, and are cloud vendor agnostic. This standard is ideal for stakeholders implementing reporting structures in a data lake environment.

Introductory course in the field of data science of the cyber education center at campus il which touches both the theoretical and the practical aspect of big data analysis in the Python language

📊 📈 Path to a free self-taught education in Data Science! 📂 📈 📈 📚

Data Science in Education Using R Book Club

Data Science Master's Programs — Top-notch postgraduate education. Taught completely in English. Top 100 worldwide.

# Bank Marketing Dataset ## Marketing Introduction: The process by which companies create value for customers and build strong customer relationships in order to capture value from customers in return. - Kotler and Armstrong (2010). Marketing campaigns are characterized by focusing on the customer needs and their overall satisfaction. Nevertheless, there are different variables that determine whether a marketing campaign will be successful or not. There are certain variables that we need to take into consideration when making a marketing campaign. ## The 4 Ps: 1) Segment of the Population: To which segment of the population is the marketing campaign going to address and why? This aspect of the marketing campaign is extremely important since it will tell to which part of the population should most likely receive the message of the marketing campaign. 2) Distribution channel to reach the customer's place: Implementing the most effective strategy in order to get the most out of this marketing campaign. What segment of the population should we address? Which instrument should we use to get our message out? (Ex: Telephones, Radio, TV, Social Media Etc.) 3) Price: What is the best price to offer to potential clients? (In the case of the bank's marketing campaign this is not necessary since the main interest for the bank is for potential clients to open depost accounts in order to make the operative activities of the bank to keep on running.) 4) Promotional Strategy: This is the way the strategy is going to be implemented and how are potential clients going to be address. This should be the last part of the marketing campaign analysis since there has to be an indepth analysis of previous campaigns (If possible) in order to learn from previous mistakes and to determine how to make the marketing campaign much more effective. ## What is a Term Deposit? A Term deposit is a deposit that a bank or a financial institurion offers with a fixed rate (often better than just opening deposit account) in which your money will be returned back at a specific maturity time. For more information with regards to Term Deposits please click on this link from Investopedia: https://www.investopedia.com/terms/t/termdeposit.asp ## Outline: 1. Import data from dataset and perform initial high-level analysis: look at the number of rows, look at the missing values, look at dataset columns and their values respective to the campaign outcome. 2. Clean the data: remove irrelevant columns, deal with missing and incorrect values, turn categorical columns into dummy variables. 3. Use machine learning techniques to predict the marketing campaign outcome and to find out factors, which affect the success of the campaign. ## Dataset Link https://archive.ics.uci.edu/ml/datasets/Bank+Marketing ## Dataset Information The data is related with direct marketing campaigns of a Portuguese banking institution. The marketing campaigns were based on phone calls. Often, more than one contact to the same client was required, in order to access if the product (bank term deposit) would be ('yes') or not ('no') subscribed. There are four datasets: 1) bank-additional-full.csv with all examples (41188) and 20 inputs, ordered by date (from May 2008 to November 2010), very close to the data analyzed in [Moro et al., 2014] 2) bank-additional.csv with 10% of the examples (4119), randomly selected from 1), and 20 inputs. 3) bank-full.csv with all examples and 17 inputs, ordered by date (older version of this dataset with less inputs). 4) bank.csv with 10% of the examples and 17 inputs, randomly selected from 3 (older version of this dataset with less inputs). The smallest datasets are provided to test more computationally demanding machine learning algorithms (e.g., SVM). The classification goal is to predict if the client will subscribe (yes/no) a term deposit (variable y). ## Attribute Information Input variables: #### bank client data: 1-age (numeric) 2-job : type of job (categorical: 'admin.','blue-collar','entrepreneur','housemaid','management','retired','self-employed','services','student','technician','unemployed','unknown') 3-marital : marital status (categorical: 'divorced','married','single','unknown'; note: 'divorced' means divorced or widowed) 4-education(categorical:'basic.4y','basic.6y','basic.9y','high.school','illiterate','professional.course','university.degree','unknown') 5-default: has credit in default? (categorical: 'no','yes','unknown') 6-housing: has housing loan? (categorical: 'no','yes','unknown') 7-loan: has personal loan? (categorical: 'no','yes','unknown') #### related with the last contact of the current campaign: 8-contact: contact communication type (categorical: 'cellular','telephone') 9-month: last contact month of year (categorical: 'jan', 'feb', 'mar', ..., 'nov', 'dec') 10-day_of_week: last contact day of the week (categorical: 'mon','tue','wed','thu','fri') 11-duration: last contact duration, in seconds (numeric). Important note: this attribute highly affects the output target (e.g., if duration=0 then y='no'). Yet, the duration is not known before a call is performed. Also, after the end of the call y is obviously known. Thus, this input should only be included for benchmark purposes and should be discarded if the intention is to have a realistic predictive model. #### other attributes: 12-campaign: number of contacts performed during this campaign and for this client (numeric, includes last contact) 13-pdays: number of days that passed by after the client was last contacted from a previous campaign (numeric; 999 means client was not previously contacted) 14-previous: number of contacts performed before this campaign and for this client (numeric) 15-poutcome: outcome of the previous marketing campaign (categorical: 'failure','nonexistent','success') #### social and economic context attributes 16-emp.var.rate: employment variation rate - quarterly indicator (numeric) 17-cons.price.idx: consumer price index - monthly indicator (numeric) 18-cons.conf.idx: consumer confidence index - monthly indicator (numeric) 19-euribor3m: euribor 3 month rate - daily indicator (numeric) 20-nr.employed: number of employees - quarterly indicator (numeric) Output variable (desired target): 21-y - has the client subscribed a term deposit? (binary: 'yes','no') ## License This dataset is public available for research. Citations - 1.Moro et al., 2014] S. Moro, P. Cortez and P. Rita. A Data-Driven Approach to Predict the Success of Bank Telemarketing. Decision Support Systems, Elsevier, 62:22-31, June 2014 2.Dua, D. and Graff, C. (2019). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.

Sri Venkateshwara University (SVU) strives to create professionals who are not only adept in academics but also in application for the benefit of humanity. We foster a culture of learning by doing. We believe in nurturing students who are at the forefront of innovation by offering an environment of research & development to make us Best University in Uttar Pradesh (UP). SVU believes in experiential learning. To facilitate this, we have an ultra-modern infrastructure that motivates students to experiment & excel in their area of interest. The Best University of Moradabad has laboratories & workshops that signify our commitment to core research, thus enabling innovation. SVU is the only institution to have set up labs in collaboration with the industry. This way we can train our students on the latest skills & make them employable. Students sharpen their practical skills under the watch full eyes of trainers & become competent professionals. For the overall development of the students, we organize cultural programs. Students take part in these programs & exhibit their talent to become confident professionals. The annual fest attracts students from all over the country & showcase their talent to make us the Top University in India. We equipped the computing labs with the latest software & hardware to augment the technical skills of the students. SVU’s library is an epitome of knowledge. It has over 3000 books & journals that ensure the students are never short on intellectual input. The team of industry trainers educate them on the key skills so crucial for employment & make us the Best University in Gajraula. The specially created engineering labs assist engineers to refine their technical acumen so much needed for the country. The Chairman Dr. Sudhir Giri believes in removing all the economic & social barriers that can hinder education. Hence, SVU provides many scholarships & grants to meritorious students. Up till now, the college has enabled over 500000 students to attain their academic desires to make us the Best Private University in Uttar Pradesh (UP). The group is running a dozen educational institutions that include medical colleges in India & abroad. Our commitment towards education & healthcare has enabled Dr Sudhir Giri to win the International Glory Man of the year Award 2021. The Best Private University in Moradabad is on the Delhi Moradabad highway, well connected with rail & road. The green surroundings provide peace of mind that enables research based learning. The carefully recruited faculty is the pride of the university. They have years of industrial & academic experience so vital for the students. They transfer key skills & make us the Best Private University in Gajraula. The faculty encourages students to undertake research & sharpen their skills that will enable them to get jobs. Majority of the faculty members are doctorates who educate the students to become competent professionals. The faculty takes part in FDP in order to develop a culture of research. The specialty of SVU is the internship. We have partnered with leading industries for providing internship to the students. We believe that education without applicability is incomplete. Students gain hands on exposure through internship & become job ready. We place most of the students during internship to make us the Top University in India. SVU, the Best University in Uttar Pradesh (UP), adopts a futuristic teaching pedagogy. We strive for experiential learning of our students through role plays, projects & presentation. The students take part in the learning activity & imbibe concepts that enable their placements. The AC seminar & conference halls allow knowledge dispersion for the development of the students. The University is running over 150 undergraduate (UG), postgraduate (PG) courses, (Ph.D.), diploma and certificate courses in various fields of Applied Sciences, Medical Science, Humanities & Social Sciences. We also run courses in Languages, Design, Agriculture, Engineering & Technology, Nursing, Pharmacy, Paramedical, Commerce & Management, Law, Library & information Sciences, Mass Comm. & Journalism to enhance the employability of the youth. SVU has a culture of project based learning. Students do projects in each semester under the guidance of faculty. They complete these projects in earmarked industries to garner hands-on skills. Through these projects, we train students on the hot skills so crucial for employment to make us the Best University in Moradabad. SVU’s Research & Development (R&D) wing encourages students to work on research areas important for the country. We have partnered with leading research institutions to undertake research. The breath-taking infrastructure of the best university in Gajraula motivates researchers to achieve their goals for research. Owing to our dedication, SVU has received grants from GOI for research on areas of national importance. The faculty members provide guidance to the scholars until they achieve their aim. We have set up the incubation center to provide fillip to new ideas that foster entrepreneurship. We want to be an institution that supports the ‘Make in India’ vision of the government. The center supports new ideas that enable the young entrepreneurs to create startups & become successful. Under the strong leadership of Dr. Sudhir Giri, till date we have successfully incubated 150 start-ups. This speaks of our exemplary education & make us the Best Private University in Uttar Pradesh (UP). These startups are not only creating wealth but also providing employment to the needy. The industrialists have lamented that the epicenter for entrepreneurship will be the educational institutions. We need to provide them with the support & infrastructure for this. The annual hackathon attracts individuals who showcase their business acumen to make us the Best Private University in Moradabad. SVU has a dedicated International Research & collaboration Cell (IRCC) that collaborates with universities abroad. Faculty & students who want to pursue studies abroad the IRCC starts admission formalities for them. We have partnered with reputed institutions for providing excellent research collaborations. Those who wish to do P. HD abroad the IRCC help them gain admission & make us the Top University in India. A lot of our faculty members are pursuing their research internationally & contributing to the welfare of humanity. SVU strives to make our students feel comfortable at the campus. Separate hostel for boys & girls with 24 hour security is available at SVU. The cafeteria serves nutritious food to the students. Gym, recreation hall & the sports ground help to relax our students & make us the Best University in Uttar Pradesh (UP). The campus has an in house ATM & convenience store for the benefit of the students. SVU enables placement through exemplary training. We train on communication & interpersonal skills in order to refine the personality of the students. We make them practice mock interviews & group discussion that help to clear placement tests. Ninety percent of the students get placed before their last semester to make us the best university in Moradabad. We have hired industrial trainers in order to provide training on block chain, machine learning, artificial intelligence (AI), and python & data science. These trainers have years of experience that enables them in training the students. The students gain key insights on these technologies & sharpen their acumen to make us the Best University in Gajraula.

DEVELOPER IT AND CYBER CENTRE DEVELOPER IT AND CYBER CENTRE Home Blog Feed Raza Samo khujlee family Awesmo speaks Open Source ProjectsMore Open Source Projects Home Blog Feed Raza Samo khujlee family Awesmo speaks Open Source Projects Open Source Projects Open Source Projects For over 20 years the Open Source Initiative (OSI) has worked to raise awareness and adoption of open source software, and build bridges between open source communities of practice. As a global non-profit, the OSI champions software freedom in society through education, collaboration, and infrastructure, stewarding the Open Source Definition (OSD), and preventing abuse of the ideals and ethos inherent to the open source movement. Open source works Inspiration Today the IT era is running and generation is very interested in working remotely to the home What it does The huge platform for the Tech geeks and the developers related to IT and data science and development to work remotely and earn the money How I built it It is a large story starting with my whole documentation and the needed and the resources that I want to do that project and what understanding to do .working on the different libraries of the java and scala on a single platform to reduce the hard code and make understandable approach for everyone .and working more efficiently as possible Challenges I ran into there were big changes that I faced during the designing face and after the design it was very tuff to implement all the interfaces and use multi-purpose API and lib to do smoothly and the backend was very horrible job that was the biggest challenge after it was the face of testing and reducing the chances of the bug and make as proficient as possible Accomplishments that I’m proud of today I have a global platform especially for Pakistani to work remotely and earn as they want on their projects without any difficulties all the payments and the resources and tools are free What I learned I can do anything if want to do nothing is impossible What’s next for FREEMEET APPLICATION I will try to give my mega project to digital Pakistan program as they can especially work on my project on for the development of my beloved country Pakistan Built With javafxml jquery location api mongodb netbeen scala springboot A description of the project and the works presented. Let’s build something together. Get in touch!

This is an open source project for the stage E of the Hamoye Data Science Internship program, cohort 2020, with real life applications in the health, engineering, demography, education and technology.

This is an open source project for the stage E of the Hamoye Data Science Internship program, cohort 2020, with real life applications in the health, engineering, demography, education and technology.

An enhanced version of the CRUD Capstone Project with Online visitors can register on-line and obtain their own password and receive a confirming e-mail that is automatically sent from the site. The code also works in the test environment on localhost. If visitors forget their password they can recover their account if they remember the hint. The email is handled by means of the PHPMailer freeware package installed using the compose package. The site was developed using the Apache2 server on localhost in the Microsoft Ubuntu extension for Windows 10 and the online site runs on nginx server in an Ubuntu cloud droplet. At the welcome page, the user can see a summary list of the profiles except for profiles made with the guest login. The Resume View page can be viewed using a link without logging in. Upon logging-in, the user can only see their own profiles. The profile information is enhanced to be more like an person's resume. There is new entry for the person's occupation. The current headline textbox is called Goals. The profile is followed by a list of the person’s skills. Skills are Skill-Set table with multiple entries for each profile is very similar to the Education table. The Skill-Set table is used in conjunction with a Skill table just as the Education table is used with an Institution table. Similarly, a major subject box was added to education. The work experience has similarly been expanded into separate company and summary blocks. There are two new database tables named Dictionary and Offensive. Extending my SQL course work, a programmed loop loaded the 11,000 word dictionary into the database from a delimited text file. The data is screened for offensive language to help make the main page suitable for a general audience, increasing the data verification performed with JavaScript for the browser and further checking at the website. After removing punctuation and exploding text phrases into an array, the information is automatically entered into the database if the words exist in the dictionary of 11,000 English words. If the words are not in the dictionary, the data is still entered into the database after further filtering for offensive words using the Offensive table. This method helps eliminate unnecessary rejections of legitimate words by reducing the need for offensive word checking. The offensive word list only exists in unreadable coded form in the database. The dictionary was constructed for my text-prediction Capstone Project using Twitter chat data for the Data Science Certificate by Johns Hopkins University on Coursera. The GitHub offensive word list of about 100 words was taken from the same project. A further enhancement was the use of JavaScript to directly construct new DOM elements based on a logical if condition for mobile device detection adding to the course project techniques of hot element insertion block as well as the jQuery append method. The inline insertion block method permits modify certain words such as edu1, edu2, ect; but the other method can change anything. An if statement could also be used with the append method so it's not clear how much direct construction of DOM elements helped and it used a number of lines of code that require a certain level of understanding.

Skin cancer is the most prevalent type of cancer. Melanoma, specifically, is responsible for 75% of skin cancer deaths, despite being the least common skin cancer. The American Cancer Society estimates over 100,000 new melanoma cases will be diagnosed in 2020. It's also expected that almost 7,000 people will die from the disease. As with other cancers, early and accurate detection—potentially aided by data science—can make treatment more effective. Currently, dermatologists evaluate every one of a patient's moles to identify outlier lesions or “ugly ducklings” that are most likely to be melanoma. Existing AI approaches have not adequately considered this clinical frame of reference. Dermatologists could enhance their diagnostic accuracy if detection algorithms take into account “contextual” images within the same patient to determine which images represent a melanoma. If successful, classifiers would be more accurate and could better support dermatological clinic work. As the leading healthcare organization for informatics in medical imaging, the Society for Imaging Informatics in Medicine (SIIM)'s mission is to advance medical imaging informatics through education, research, and innovation in a multi-disciplinary community. SIIM is joined by the International Skin Imaging Collaboration (ISIC), an international effort to improve melanoma diagnosis. The ISIC Archive contains the largest publicly available collection of quality-controlled dermoscopic images of skin lesions. In this competition, you’ll identify melanoma in images of skin lesions. In particular, you’ll use images within the same patient and determine which are likely to represent a melanoma. Using patient-level contextual information may help the development of image analysis tools, which could better support clinical dermatologists. Melanoma is a deadly disease, but if caught early, most melanomas can be cured with minor surgery. Image analysis tools that automate the diagnosis of melanoma will improve dermatologists' diagnostic accuracy. Better detection of melanoma has the opportunity to positively impact millions of people.

MAN PROBLEM? Technology advancement to address the world’s rising demand for clean and reasonable power will need simultaneous improvements in materials science and technology in order to meet the achievement demands of new power-generating systems. For instance, a technological advance in the wireless broadband industry might enable more productive use of insufficient range, resulting in greater speed and capability for wireless broadband There are so numerous methods technological advancements have improved humanity, save time and cost of production. Our individual life is now massively dependent on technology and technology has advanced with years and transformed the way we practice, travel, socialize, educate our children live, and buy products. As somebody’s demands for developing technology recommence, the Institute of Electrical and Electronics Engineers (IEEE’s) presents a clear knowledge as an industry ready to continue developing patterns for the computer and science industry that foster technological discovery and perfection for the benefit of humanity. Advancing technology for the advantage of humanity Technology transforms the way individuals talk, learn, and imagine. It helps the community and ascertains show people cooperate with each other on a periodic basis. Technology plays a vital role in society. The invention of the internet supplies us access to data at a twenty-four-hour rate and you have access to almost anything online. technological advancements initiated learning more entertainment and beneficial. Technology brought many new modes of electronic intelligence. For example, there is social networking, emails. you can facetime a personality that lives on the other side of the globe, and there’s video conferencing where you can have discussions electronically. There are many innovative apps on telephones that although characters to watch their weight, how many calories they intake, their heart rate and other health resources any time of the day. technology provides us with a lot of educational content, fast and free, which makes the learning process more personalized and self-paced, improving it. technology has made life easier mostly for those who get the chance to interact with it. For instance use of social media or websites in our daily lives. young people who become addicted to social media ( media platforms such as TikTok, Instagram, Twitter, Facebook, Snapchat and others are highly addictive, and YouTube can also be grouped into this category. Every time a person takes engagement via a “comment” “follow” or “like” somebody’s brain delivers feel-good neurotransmitters, eventually resulting in wanting more engagement). they crave to cope with the dynamic society where outward appearance is highly regarded. They do all kinds of things in order to become successful and get more likes some even grow cyberbullied because of their visions. This is why modern people suffer more from grief to the point of suicide. HOW ADVANCED TECHNOLOGY HAS ADDED THE MAN’S PROBLEM? Humans are the most magnificent piece of God. Nature has given humans all the demanded things that they required. But the eagerness of humans was not fulfilled. They started making technology in order to get their work done more spontaneously. There are so many interests in Technology. But remember if there is a benefit, there problem also. So the obstacle is people became inactive because of technology. Nowadays, we do not go to the supermarket to purchase groceries rather than order them online. We didn’t go out and meet our associates “face to face” alternatively that we meet them on social media “ONLINE” or “LIVE”. The human mind has built technology but now technology is destroying our minds. Technology has also created some new complications for humans. We don’t believe in our own people instead we consider technology which can be replaced by itself also. Nowadays, there are several Hackers on the Internet. They can take your secret data also. Conclusion. we are in the epoch of globalization, where technologies will always be done, and these have designed a great change in human action, either for good or for bad. Technology has promoted many things, and entering in context has served much, in distance education; however, technology can become serious because sometimes it can create problems for the man if it is not used suitably, following rules of their use.

This is an open source project for the stage E of the Hamoye Data Science Internship program, cohort 2020, with real life applications in the health, engineering, demography, education and technology.

This is an open source project for the stage E of the Hamoye Data Science Internship program, cohort 2020, with real life applications in the health, engineering, demography, education and technology.

Volunteering Experience: This is a mobile application developed in Ionic 3 and Angular 4 with firebase and AngularFire for Science and Technology Education Program(STEP) which will be used for registration of the students for Robotics competition. The application is integrated with Firebase database to store the data.

Summary In this article, we are going to present the solution for the Women’s Health Risk Assessment data science competition on Microsoft’s Cortana Intelligence platform which was ranked among the top 5%. In this page, you can find the published Azure ML Studio experiment., a description of the data science process used, and finally a link to the R code (in GitHub). Competition Here is the description from the Microsoft Cortana Competition “To help achieve the goal of improving women's reproductive health outcomes in underdeveloped regions, this competition calls for optimized machine learning solutions so that a patient can be accurately categorized into different health risk segments and subgroups. Based on the categories that a patient falls in, healthcare providers can offer an appropriate education and training program to patients. Such customized programs have a better chance to help reduce the reproductive health risk of patients. This dataset used in this competition was collected via survey in 2015 as part of a Bill & Melinda Gates Foundation funded project exploring the wants, needs, and behaviors of women and girls with regards to their sexual and reproductive health in nine geographies. The objective of this machine learning competition is to build machine learning models to assign a young woman subject (15-30 years old) in one of the 9 underdeveloped regions into a risk segment, and a subgroup within the segment.” https://gallery.cortanaintelligence.com/Competition/Womens-Health-Risk-Assessment-1 Dataset The contains 9000 observations The original training dataset is in CSV format and can be found in the competition’s description. To submit a solution, two options are possible: build it in Azure ML Studio or build your solutions locally in R and then submit it through Azure ML Studio. An Azure ML’s solution, and a R script code where given as example. The two solutions are based on the use of a Generalized Linear Model is automatically downloaded. You can find a detailed description of the dataset, the R sample Code and a tutorial using Azure ML and R in the competition page Solution I started following the R tutorial for this competition. Then I have submitted the exact same R solution. The sample model has a 77% accuracy Pre-processing & Cleaning The first thing I did was changing the initial multinomial model (nnet package) for a random forest model (RandomForest package). All missing values have been replaced by 0 Feature selection Features have been selected using the function varImpPlot from the randomforest package Parameter tuning I have chosen (for educational matter) to use the module Tune Model Hyperparameters in Azure ML Studio. I could have also used the R Package Caret. Evaluation The final model has an accuracy of 86.36% (18 position over almost 500 participants) You can download the R code here

This is an open source project for the stage E of the Hamoye Data Science Internship program, cohort 2020, with real life applications in the health, engineering, demography, education and technology.

This is an open source project for the stage E of the Hamoye Data Science Internship program, cohort 2020, with real life applications in the health, engineering, demography, education and technology.