Deep Learning Drizzle:几乎所有 AI 免费课程都在这里

MaughamLawrence 发布于1月前 阅读490次
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:balloon: :tada: Deep Learning Drizzle :confetti_ball: :balloon:

Contents

:tada: Deep Learning :confetti_ball: :balloon:

S.No Course Name University/Instructor(s) Course WebPage Lecture Videos Year
1. Neural Networks for Machine Learning Geoffrey Hinton, University of Toronto Lecture-Slides CSC321-tijmen YouTube-Lectures UofT-mirror 2012 2014
2. Neural Networks Demystified Stephen Welch, Welch Labs Supplementary Code YouTube-Lectures 2014
3. Deep Learning at Oxford Nando de Freitas, Oxford University Oxford-ML YouTube-Lectures 2015
4. CS231n: CNNs for Visual Recognition Andrej Karpathy, Stanford University CS231n None 2015
5. CS231n: CNNs for Visual Recognition Andrej Karpathy, Stanford University CS231n YouTube-Lectures 2016
6. CS231n: CNNs for Visual Recognition Justin Johnson, Stanford University CS231n YouTube-Lectures 2017
7. CS224d: Deep Learning for NLP Richard Socher, Stanford University CS224d YouTube-Lectures 2015
8. CS224d: Deep Learning for NLP Richard Socher, Stanford University CS224d YouTube-Lectures 2016
9. CS224n: NLP with Deep Learning Richard Socher, Stanford University CS224n YouTube-Lectures 2017
10. Neural Networks Hugo Larochelle, Université de Sherbrooke Neural-Networks YouTube-Lectures 2016
11. Deep Learning Andrew Ng, Stanford University CS230 None 2018
           
12. Bay Area Deep Learning Many legends, Stanford None YouTube-Lectures 2016
13. UvA Deep Learning Efstratios Gavves, University of Amsterdam(UvA) UvA-DLC Lecture-Videos 2018
14. Advanced Deep Learning and Reinforcement Learning Many legends, DeepMind None YouTube-Lectures 2018
15. Deep Learning Francois Fleuret, EPFL EE-59 None 2019
16. Deep Learning Francois Fleuret, EPFL EE-59 Video-Lectures 2018
17. Deep Learning for Perception Dhruv Batra, Virginia Tech ECE-6504 YouTube-Lectures 2015
18. Introduction to Deep Learning Alexander Amini, Harini Suresh, MIT 6.S191 YouTube-Lectures 2018
19. Deep Learning for Self-Driving Cars Lex Fridman, MIT 6.S094 YouTube-Lectures 2017-2018
20. MIT Deep Learning Many Researchers, Lex Fridman, MIT 6.S094, 6.S091, 6.S093 YouTube-Lectures 2019
21. Introduction to Deep Learning Biksha Raj and many others, CMU 11-485/785 YouTube-Lectures S2018
22. Introduction to Deep Learning Biksha Raj and others, CMU 11-485/785 YouTube-Lectures Recitation-Inclusive F2018
23. Deep Learning Specialization Andrew Ng, Stanford DeepLearning.AI YouTube-Lectures 2017-2018
24. Deep Learning Ali Ghodsi, University of Waterloo STAT-946 YouTube-Lectures F2015
25. Deep Learning Ali Ghodsi, University of Waterloo STAT-946 YouTube-Lectures F2017
26. Deep Learning Mitesh Khapra, IIT-Madras CS7015 YouTube-Lectures 2018
27. Deep Learning for AI UPC Barcelona DLAI-2017 DLAI-2018 YouTube-Lectures 2017-2018
           
-2. Deep Learning Book companion videos Ian Goodfellow and others DL-book slides YouTube-Lectures 2017
-1. Neural Networks Grant Sanderson None YouTube-Lectures 2017-2018
           

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:cupid: Machine Learning Fundamentals :cyclone: :boom:

S.No Course Name University/Instructor(s) Course Webpage Video Lectures Year
1. Linear Algebra Gilbert Strang, MIT 18.06 SC YouTube-Lectures 2011
2. Linear Algebra: An in-depth Introduction Pavel Grinfeld None Part-1 Part-2 Part-3 Part-4 2015- 2017
3. Essence of Linear Algebra Grant Sanderson None YouTube-Lectures 2016
4. Essence of Calculus Grant Sanderson None YouTube-Lectures 2017-2018
5. Mathematics for Machine Learning (Linear Algebra, Calculus) David Dye, Samuel Cooper, and Freddie Page, IC-London MML YouTube-Lectures 2018
6. Machine Learning Fundamentals Sanjoy Dasgupta, UC-San Diego MLF-slides YouTube-Lectures 2018
           
           

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:cupid: Optimization for Machine Learning :cyclone: :boom:

S.No Course Name University/Instructor(s) Course Webpage Video Lectures Year
1. Optimization for Machine Learning S V N Vishwanathan, Purdue University None YouTube-Lectures 2011
2. Optimization Geoff Gordon & Ryan Tibshirani, CMU 10-725 YouTube-Lectures 2012
3. Convex Optimization Ryan Tibshirani, CMU cvx-opt YouTube-Lectures F2018
4. Convex Optimization Stephen Boyd, Stanford University ee364a YouTube-Lectures 2008
5. Modern Algorithmic Optimization Yurii Nesterov, UCLouvain None YouTube-Lectures 2018
           

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:cupid: General Machine Learning :cyclone: :boom:

S.No Course Name University/Instructor(s) Course Webpage Video Lectures Year
1. CS229: Machine Learning Andrew Ng, Stanford University CS229-old CS229-new YouTube-Lectures 2007
2. Machine Learning and Data Mining Nando de Freitas, University of British Columbia CPSC-340 YouTube-Lectures 2012
3. Learning from Data Yaser Abu-Mostafa, CalTech CS156 YouTube-Lectures 2012
4. Machine Learning Rudolph Triebel, TUM Machine Learning YouTube-Lectures 2013
5. Pattern Recognition Sukhendu Das, IIT-M and C.A. Murthy, ISI-Calcutta PR-NPTEL YouTube-Lectures 2014
6. Introduction to Machine Learning Katie Malone, Sebastian Thrun, Udacity ML-Udacity YouTube-Lectures 2015
7. Introduction to Machine Learning Dhruv Batra, Virginia Tech ECE-5984 YouTube-Lectures 2015
8. Statistical Learning - Classification Ali Ghodsi, University of Waterloo STAT-441 YouTube-Lectures 2015
9 Machine Learning Theory Shai Ben-David, University of Waterloo None YouTube-Lectures 2015
10. Introduction to Machine Learning Alex Smola, CMU 10-701 YouTube-Lectures S2015
11. ML: Supervised Learning Michael Littman, Charles Isbell, Pushkar Kolhe, GaTech ML-Udacity YouTube-Lectures 2015
12. ML: Unsupervised Learning Michael Littman, Charles Isbell, Pushkar Kolhe, GaTech ML-Udacity YouTube-Lectures 2015
13. Statistical Machine Learning Larry Wasserman, CMU None YouTube-Lectures S2016
14. Statistical Learning - Classification Ali Ghodsi, University of Waterloo None YouTube-Lectures 2017
15. Machine Learning Andrew Ng, Stanford University Coursera-ML YouTube-Lectures 2017
16. Statistical Machine Learning Ryan Tibshirani, Larry Wasserman, CMU 10-702 YouTube-Lectures S2017
17. Machine Learning for Intelligent Systems Kilian Weinberger, Cornell University CS4780 YouTube-Lectures F2018
18. Statistical Learning Theory and Applications Tomaso Poggio, Lorenzo Rosasco, Sasha Rakhlin 9.520/6.860 YouTube-Lectures F2018
19. Machine Learning and Data Mining Mike Gelbart, University of British Columbia CPSC-340 YouTube-Lectures 2018
20. Foundations of Machine Learning David Rosenberg, Bloomberg FOML YouTube-Lectures 2018
21. Introduction to Machine Learning Andreas Krause, ETH Zuerich IntroML YouTube-Lectures 2018
22. Advanced Machine Learning Joachim Buhmann, ETH Zuerich AML-18 YouTube-Lectures 2018
           
           

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:balloon: Reinforcement Learning :hotsprings: :video_game:

S.No Course Name University/Instructor(s) Course Webpage Video Lectures Year
1. Short Course on Reinforcement Learning Satinder Singh, UMichigan None YouTube-Lectures 2011
2. Approximate Dynamic Programming Dimitri P. Bertsekas, MIT Lecture-Slides YouTube-Lectures 2014
3. Introduction to Reinforcement Learning David Silver, DeepMind UCL-RL YouTube-Lectures 2015
4. Reinforcement Learning Charles Isbell, Chris Pryby, GaTech; Michael Littman, Brown RL-Udacity YouTube-Lectures 2015
5. Reinforcement Learning Balaraman Ravindran, IIT Madras RL-IITM YouTube-Lectures 2016
6. Deep Reinforcement Learning Sergey Levine, UC Berkeley CS-294 YouTube-Lectures S2017
7. Deep Reinforcement Learning Sergey Levine, UC Berkeley CS-294 YouTube-Lectures F2017
8. Deep RL Bootcamp Many legends, UC Berkeley Deep-RL YouTube-Lectures 2017
9. Deep Reinforcement Learning Sergey Levine, UC Berkeley CS-294-112 YouTube-Lectures 2018
10. Reinforcement Learning Pascal Poupart, University of Waterloo CS-885 YouTube-Lectures 2018
11. Deep Reinforcement Learning and Control Katerina Fragkiadaki and Tom Mitchell, CMU 10-703 YouTube-Lectures 2018
           
           

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:loudspeaker: Probabilistic Graphical Models - (Foundation for Graph Neural Networks) :sparkles:

S.No Course Name University/Instructor(s) Course WebPage Lecture Videos Year
1. Probabilistic Graphical Models Many Legends, MPI-IS MLSS-Tuebingen YouTube-Lectures 2013
2. Probabilistic Modeling and Machine Learning Zoubin Ghahramani, University of Cambridge WUST-Wroclaw YouTube-Lectures 2013
3. Probabilistic Graphical Models Eric Xing, CMU 10-708 YouTube-Lectures 2014
4. Learning with Structured Data: An Introduction to Probabilistic Graphical Models Christoph Lampert, IST Austria None YouTube-Lectures 2016
5. Probabilistic Graphical Models Nicholas Zabaras, University of Notre Dame PGM YouTube-Lectures 2018
           
           

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:hibiscus: Natural Language Processing - (More Applied) :cherry_blossom: :sparkling_heart:

S.No Course Name University/Instructor(s) Course WebPage Lecture Videos Year
1. Deep Learning for Natural Language Processing Nils Reimers, TU Darmstadt DL4NLP YouTube-Lectures 2015-2017
2. Deep Learning for Natural Language Processing Many Legends, DeepMind-Oxford DL-NLP YouTube-Lectures 2017
3. Deep Learning for Speech & Language UPC Barcelona DL-SL Lecture-Videos 2017
4. Neural Networks for Natural Language Processing Graham Neubig, CMU NN4NLP Code YouTube-Lectures 2017
5. Neural Networks for Natural Language Processing Graham Neubig, CMU NN4-NLP YouTube-Lectures 2018
6. Neural Networks for Natural Language Processing Graham Neubig, CMU NN4NLP YouTube-Lectures 2019
           
           

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Automatic Speech Recognition :speech_balloon: :thought_balloon:

S.No Course Name University/Instructor(s) Course WebPage Lecture Videos Year
1. Deep Learning for Speech & Language UPC Barcelona DL-SL Lecture-Videos YouTube-Videos 2017
2. Speech and Audio in the Northeast Many Legends, Google NYC SANE-15 YouTube-Videos 2015
3. Speech and Audio in the Northeast Many Legends, Google NYC SANE-17 YouTube-Videos 2017
4. Speech and Audio in the Northeast Many Legends, Google Cambridge SANE-18 YouTube-Videos 2018
           
-1. Deep Learning for Speech Recognition Many Legends, AoE None YouTube-Videos 2015-2018

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:fire: Modern Computer Vision :movie_camera:

S.No Course Name University/Instructor(s) Course WebPage Lecture Videos Year
1. Computer Vision - (classical) Mubarak Shah, UCF CAP-5415 YouTube-Lectures 2012
2. Computer Vision - (classical) Mubarak Shah, UCF CAP-5415 YouTube-Lectures 2014
3. Introduction to Computer Vision (foundation) Aaron Bobick, Irfan Essa, Arpan Chakraborty CV-Udacity YouTube-Lectures 2016
4. Autonomous Navigation for Flying Robots Juergen Sturm, TUM Autonavx YouTube-Lectures 2014
5. SLAM - Mobile Robotics Cyrill Stachniss, Universitaet Freiburg RobotMapping YouTube-Lectures 2014
           
6. Deep Learning for Computer Vision UPC Barcelona DLCV-16 DLCV-17 DLCV-18 YouTube-Lectures 2016-2018
7. Convolutional Neural Networks Andrew Ng, Stanford University DeepLearning.AI YouTube-Lectures 2017
8. Variational Methods for Computer Vision Daniel Cremers, TUM VMCV YouTube-Lectures 2017
9. Winter School on Computer Vision Lots of Legends, Israel Institute for Advanced Studies WS-CV YouTube-Lectures 2017
10. Deep Learning for Visual Computing Debdoot Sheet, IIT-Kgp Nptel Notebooks YouTube-Lectures 2018
           

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:star2: Boot Camps or Summer Schools :maple_leaf:

S.No Course Name University/Instructor(s) Course WebPage Lecture Videos Year
1. Deep Learning, Feature Learning Lots of Legends, IPAM UCLA GSS-2012 YouTube-Lectures 2012
2. Big Data Boot Camp Many Legends, Simons Institute Big Data YouTube-Lectures 2013
3 Mathematics of Signal Processing Many Legends, Hausdorff Institute for Mathematics SigProc YouTube-Lectures 2016
4. Microsoft Research - Machine Learning Course S V N Vishwanathan and Prateek Jain MS-Research None YouTube-Lectures 2016
5. Deep Learning Summer School Lots of Legends, Université de Montréal DL-SS-16 YouTube-Lectures 2016
6. Machine Learning Advances and Applications Seminar Lots of Legends, Fields Institute, University of Toronto MLAAS YouTube-Lectures Video-Lectures 2016-2017
7. Machine Learning Advances and Applications Seminar Lots of Legends, Fields Institute, University of Toronto MLAAS Video Lectures 2017-2018
8. Representation Learning Many Legends, Simons Institute RepLearn YouTube-Lectures 2017
9. Foundations of Machine Learning Many Legends, Simons Institute ML-BootCamp YouTube-Lectures 2017
10. Optimization, Statistics, and Uncertainty Many Legends, Simons Institute Optim-Stats YouTube-Lectures 2017
11. Deep Learning: Theory, Algorithms, and Applications Many Legends, TU-Berlin DL: TAA YouTube-Lectures 2017
12. Foundations of Data Science Many Legends, Simons Institute DS-BootCamp YouTube-Lectures 2018
13. Deep|Bayes Many Legends, HSE Moscow DeepBayes.ru YouTube-Lectures 2018
14. New Deep Learning Techniques Many Legends, IPAM UCLA IPAM-Workshop YouTube-Lectures 2018
15. Machine Learning Advances and Applications Seminar Lots of Legends, Fields Institute, University of Toronto MLASS Video Lectures 2018-2019
16. MIFODS- ML, Stats, ToC seminar Lots of Legends, MIT MIFODS-seminar Lecture-videos 2018-2019
           

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:bird: Bird's Eye view of A(G)I

S.No Course Name University/Instructor(s) Course WebPage Lecture Videos Year
1. Artificial General Intelligence Lots of Legends, MIT 6.S099-AGI Lecture-Videos 2018-2019
2. AI Podcast Lots of Legends, MIT AI-Pod YouTube-Lectures 2018-2019
           

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To-Do :runner:

:white_large_square:️ Optimization courses which form the foundation for ML, DL, RL

:white_large_square:️ Computer Vision courses which are DL & ML heavy

:white_large_square:️ NLP courses which are DL, RL, & ML heavy

:white_large_square:️ Speech recognition courses which are DL heavy

:white_large_square:️ Courses on Graph Neural Networks

:white_large_square:️ Section on DL/RL/ML Summer School Lectures

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Contributions :pray:

If you find a course that fits in any of the above categories (i.e. DL, ML, RL, CV, NLP), and the course has lecture videos (with slides - optional), then please raise an issue or send a PR by updating the course according to the above format.

Danke Sehr!

:gift_heart: :mortar_board: :mortar_board: :mortar_board: :mortar_board: :mortar_board: :mortar_board: :mortar_board: :mortar_board: :mortar_board: :mortar_board: :gift_heart:

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