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

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Economically Inclusive Models encourage the participation of local community labor through a holistic approach that includes skill development and the foundations of resource management which develops quality of life through wealth creation and the expansion of markets. Raw material is returned to the people in the form of new products. Throughout the course of human history, it has frequently become necessary for nations to dissolve and or restructure economic systems and adjust strategies which have proven to be ineffective in stimulating development, growth and economic prosperity as economies and times change technologically. When the policies are and continually becoming increasingly oppressive in nature and exist against the natural law and the psychology of human inspiration, and are only enforced through deception and the use of force by indoctrinated constituencies, they begin to separate people from their natural desires to achieve, thrive, and prosper. Often economic development and social programs are implemented under the guise of prosperity only to be concealing the true intent of enslavement for the populace and a theft of resources. This is in defiance of the power of truth which is based on the laws of nature and of nature's right to full expression of humanity, which God entitles to all men and women. This deception is fraudulent and criminal in nature and is the equivalent of murder, for it robs humanity of its right to self-actualization, cognizant development and the realization of self-worth. The main principle behind the current economic agenda being implanted throughout the world in an effort to bring about a new economic world order, is a belief that the effective use of force and the stringent control of natural resources is the key to creating and maintaining economic power and further serves to manipulate markets by creating fictional gaps in supply and demand. This 'order out of chaos' model has been a standard for centuries. The problem is that it is based on the principles of suppression and oppression, which are implemented and maintained using force and highly supported with deception through disinformation, propaganda and oppressive operations aimed at reducing the natural expression of humanity, freedom, and independence. This is a sign of fear and incompetence stemming from the conditioning of the past age of scarcity by those in power because it is inconsistent with natural law, which supports full expression as a means of achievement. Natural power relies on truth and does not require deception to be maintained. It stands on its own accord. Power encourages a population to achieve self-actualization and economic prosperity which is reflective of a strong middle class, economic and social growth as well as development. It is a natural spiritual expression in alignment with truth and does not require manipulation to be maintained. On the other hand, there is no positive natural expression for force as it is inherently weaker and short term, its goal is to hinder the natural power of the people from being fully expressed. This is a lower spiritual form of thought and achievement that is inherently inferior to just power and is only sustained through deceptive practices. It essentially further weakens its followers & leaders and subsequently results in wide disparities of wealth and the elimination of the middle class that is necessary to maintain stability and economic growth, especially in a consumer based economy. The belief that people need to be largely suppressed is highly limiting to a society and ensures a lower expression of associated economic achievement inhibiting humanities growth and development on all levels. More specifically it inhibits the development of free creative minds, their contributions of intellectual property and innovation. The irresponsible use of natural resources is equally discouraging. We are blessed with an abundance of agricultural land, potential energy sources from wind, solar, geothermal, wave & or tidal power and vast basic materials such as cement, brick, wood, and rock that would easily address any structural and infrastructural needs. What is lacking is proper accounting and utilization of the vast natural resources readily available and the reliance on utilizing goods and services that could easily be provided in the local market rather than relying on imports. Years of war and internal conflict have created a gap in productive and practical knowledge in many regions of the world. This knowledge gap can be reconciled through the incorporation of trade schools that emphasize the reduction of imports through the utilization of what is natural to the region, while cognizant of unintended environmental consequences (such as those of using good farming topsoil for mud bricks). Building and architecturally designing structures as well as much needed infrastructure with the concept of maximum utilization of the natural resources native to the region offering a common-sense solution to the vast imbalance of trade challenges in agriculture, materials, labor, management, and expertise. This would also allow for the use of mineral profits to be used to barter for higher goods that would enhance the quality of life rather than being allocated to provide for mere survival and resulting in continued dependence. The global economy although growing extensively in a number of sectors and regions is still oppressive in nature with significant barriers to entry and managed by an overburdened government and economic system that primarily operates to diminish the prospects of the peoples growth and focuses gains and bailouts on only a few elite. The means of gaining economic control through manipulative programing of the masses is essentially killing humanities best prospects for a shared prosperous future. It is equally discouraging to find education not matching the needs of the emerging technological environment. In regions, largely in a development mode, it is necessary to focus the majority of educational emphasis on developing trade schools that can instantly impact job growth and prosperity. Affecting positively these educational concerns in developing nations now, will yield significantly improved outcomes locally, regionally and beyond, further improving psychological perceptions globally. The idea that people need to be controlled and oppressed through negative conditioning that simply thwarts achievement and ambitions is a system doomed to fail. Nothing can be achieved in the current economic system described except for chaos and the limited order maintained through fear, deception, propaganda and the manipulation of the herd or collective mentality / perception. As a result of these policies that have been implemented worldwide, we now have a world that is largely a police state and unaware of truth or its own power due to a constant flow of manipulative disinformation and propaganda. This is a grand reflection of the use of force, deception, and oppression and we see its expression in the deterioration of our economic systems and basic freedoms inherent from God. Highlights The following demonstrates the financial projections of our five primary business models. Estimates do not take into account possibilities of above average returns with many investment options that we currently have at our disposal. 1. Logistics to include shipping, security, courier service and inclusive A to B deployment of human and other resources or assets. 2. Financial to include international developmental finance, banking & credit unions, insurance and brokerage of securities. 3. Commodities to include strategic minerals (rare earths), lumber, etc... 4. Consulting to include strategic government, intelligence, business and educational. 5. Investments to include unique platforms, vehicles, traditional models, land, infrastructure, research and development. ECONOMIC STIMULUS PLAN The Economic Stimulus plan - build... Further expansion of and clarity continues to be encouraged.

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