README.md

? Deep Learning Drizzle ?

S.No Course Name University/Teacher(s) Course WebPage Lecture Videos Year 1. Neural Networks for Machine Learning Geoffrey Hinton, University of Toronto Lecture-Slides
CSC321-tijmen YouTube-Lectures
mirror 2012
2014 2. Deep Learning at Oxford Nando de Freitas, Oxford University Oxford-ML YouTube-Lectures 2015 3. CS231n: CNNs for Visual Recognition Andrej Karpathy, Stanford University CS231n None 2015 4. CS231n: CNNs for Visual Recognition Andrej Karpathy, Stanford University CS231n YouTube-Lectures 2016 5. CS231n: CNNs for Visual Recognition Justin Johnson, Stanford University CS231n YouTube-Lectures 2017 6. CS224d: Deep Learning for NLP Richard Socher, Stanford University CS224d YouTube-Lectures 2015 7. CS224d: Deep Learning for NLP Richard Socher, Stanford University CS224d YouTube-Lectures 2016 8. CS224n: NLP with Deep Learning Richard Socher, Stanford University CS224n YouTube-Lectures 2017 9. Neural Networks Hugo Larochelle, Université de Sherbrooke Neural-Networks YouTube-Lectures 2016 10. CS229: Machine Learning Andrew Ng, Stanford University CS229 YouTube-Lectures-2014 2017 11. Deep Learning Andrew Ng, Stanford University CS230 None 2018 12. Bay Area Deep Learning Many legends 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 Spring-2018 22. Introduction to Deep Learning Biksha Raj and others, CMU 11-485/785 YouTube-Lectures Fall-2018 23. Deep Learning Specialization Andrew Ng, Stanford DeepLearning.AI YouTube-Lectures 2017-2018

24. Deep Learning, Feature Learning Many legends, IPAM UCLA GSS-2012 YouTube-Lectures 2012 25. New Deep Learning Techniques Many Legends, IPAM UCLA IPAM-Workshop YouTube-Lectures 2018 26. Deep|Bayes Many Legends DeepBayes.ru YouTube-Lectures 2018

?General Machine Learning ?

S.No Course Name University/Teacher(s) Course Webpage Video Lectures Year 1. Learning from Data Yaser Abu-Mostafa, CalTech CS156 YouTube-Lectures 2012 2. Machine Learning Rudolph Triebel, TUM Machine Learning YouTube-Lectures 2013 3. Introduction to Machine Learning Dhruv Batra, Virginia Tech ECE-5984 YouTube-Lectures 2015 4. Machine Learning Andrew Ng, Stanford University Coursera-ML YouTube-Lectures 2017

?Reinforcement Learning ♨️?

S.No Course Name University/Teacher(s) Course Webpage Video Lectures Year 1. Approximate Dynamic Programming Dimitri P. Bertsekas Lecture-Slides YouTube-Lectures 2014 2. Introduction to Reinforcement Learning David Silver, DeepMind UCL-RL YouTube-Lectures 2015 3. Reinforcement Learning Balaraman Ravindran, IIT Madras RL-IITM YouTube-Lectures 2016 4. Deep Reinforcement Learning Sergey Levine, UC Berkeley CS-294 YouTube-Lectures Spring-2017 5. Deep Reinforcement Learning Sergey Levine, UC Berkeley CS-294 YouTube-Lectures Fall-2017 6. Deep Reinforcement Learning Sergey Levine, UC Berkeley CS-294-112 YouTube-Lectures 2018 7. Deep RL Bootcamp Many legends Deep-RL YouTube-Lectures 2017 8. Reinforcement Learning Pascal Poupart, University of Waterloo CS-885 YouTube-Lectures 2018 9. Deep Reinforcement Learning and Control Katerina Fragkiadaki and Tom Mitchell, CMU 10-703 YouTube-Lectures 2018

?Probabilistic Graphical Models - (Foundation for Graph Neural Networks) ✨

S.No Course Name University/Teacher(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. Probabilistic Graphical Models Nicholas Zabaras, University of Notre Dame PGM-S2018 YouTube-Lectures 2018

?Natural Language Processing - (More Applied) ?

S.No Course Name University/Teacher(s) Course WebPage Lecture Videos Year 1. Deep Learning for Natural Language Processing Many Legends, DeepMind-Oxford DL-NLP YouTube-Lectures 2017 2. Neural Networks for Natural Language Processing Graham Neubig, CMU NN4NLP YouTube-Lectures 2017 3. Neural Networks for Natural Language Processing Graham Neubig, CMU NN4-NLP YouTube-Lectures 2018 4. Neural Networks for Natural Language Processing Graham Neubig, CMU NN4NLP YouTube-Lectures 2019

?Modern Computer Vision ??

S.No Course Name University/Teacher(s) Course WebPage Lecture Videos Year 1. Convolutional Neural Networks Andrew Ng, Stanford DeepLearning.AI YouTube-Lectures 2017 2. Variational Methods for Computer Vision Daniel Cremers, TUM VMCV YouTube-Lectures 2017 3. Deep Learning for Visual Computing Debdoot Sheet, IIT-Kgp Nptel
Notebooks YouTube-Lectures 2018 4. Autonomous Navigation for Flying Robots Juergen Sturm, TUM Autonavx YouTube-Lectures 2014 5. SLAM - Mobile Robotics Cyrill Stachniss, Universitaet Freiburg RobotMapping YouTube 2014

To-Do ?

⬜️ Computer Vision courses which are DL & ML heavy

⬜️ NLP courses which are DL, RL, & ML heavy

⬜️ Speech recognition courses which are DL heavy

⬜️ Add courses on Graph Neural Networks

⬜️ Add DL/RL Summer School lectures

Contributions ?

If you find a course that fits in any of the three categories above (i.e. DL, ML, RL), 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.

Thanks!