🎈 🎉 Deep Learning Drizzle 🎊 🎈

📚 "Read enough so you start developing intuitions and then trust your intuitions and go for it!" 📚 ​
Prof. Geoffrey Hinton, University of Toronto

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Contents

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• Deep Learning (Deep Neural Networks) ⤵️

• Machine Learning Fundamentals ⤵️

• Optimization for Machine Learning ⤵️

• General Machine Learning ⤵️

• Reinforcement Learning ⤵️

• Probabilistic Graphical Models ⤵️

• Natural Language Processing ⤵️

• Automatic Speech Recognition ⤵️

• Modern Computer Vision ⤵️

• Boot Camps or Summer Schools ⤵️

• Bird's Eye view of Artificial (General) Intelligence ⤵️

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🎉 Deep Learning (Deep Neural Networks) 🎊 🎈

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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	Suppl. 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	Bhiksha Raj and many others, CMU	11-485/785	YouTube-Lectures	S2018
22.	Introduction to Deep Learning	Bhiksha Raj and others, CMU	11-485/785	YouTube-Lectures Recitation-Inclusive	F2018
23.	Deep Learning Specialization	Andrew Ng, Stanford	DL.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
28.	Deep Learning Book companion videos	Ian Goodfellow and others	DL-book slides	YouTube-Lectures	2017
29.	Neural Networks	Grant Sanderson	None	YouTube-Lectures	2017-2018
30.	Deep Learning	Alex Bronstein and Avi Mendelson, Technion	CS236605	YouTube-Lectures	2018

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💘 Machine Learning Fundamentals 🌀 💥

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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.	Probability Primer	Jeffrey Miller (mathematical monk), Brown University	None	YouTube-Lectures	2011
3.	Probability and Statistics	Michel van Biezen	None	YouTube-Lectures	2015
4.	Linear Algebra: An in-depth Introduction	Pavel Grinfeld	None	Part-1 Part-2 Part-3 Part-4	2015- 2017
5.	Essence of Linear Algebra	Grant Sanderson	None	YouTube-Lectures	2016
6.	Essence of Calculus	Grant Sanderson	None	YouTube-Lectures	2017-2018
7.	Mathematics for Machine Learning (Linear Algebra, Calculus)	David Dye, Samuel Cooper, and Freddie Page, IC-London	MML	YouTube-Lectures	2018
8.	Machine Learning Fundamentals	Sanjoy Dasgupta, UC-San Diego	MLF-slides	YouTube-Lectures	2018

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💘 Optimization for Machine Learning 🌀 💥

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S.No	Course Name	University/Instructor(s)	Course Webpage	Video Lectures	Year
1.	Convex Optimization	Stephen Boyd, Stanford University	ee364a	YouTube-Lectures	2008
2.	Optimization for Machine Learning	S V N Vishwanathan, Purdue University	None	YouTube-Lectures	2011
3.	Optimization	Geoff Gordon & Ryan Tibshirani, CMU	10-725	YouTube-Lectures	2012
4.	Convex Optimization	Joydeep Dutta, IIT-Kanpur	cvx-nptel	YouTube-Lectures	2013
5.	Algorithmic Aspects of Machine Learning	Ankur Moitra, MIT	18.409-AAML	YouTube-Lectures	S2015
6.	Advanced Algorithms	Ankur Moitra, MIT	6.854-AA	YouTube-Lectures	S2016
7.	Convex Optimization	Ryan Tibshirani, CMU	cvx-opt	YouTube-Lectures	F2018
8.	Modern Algorithmic Optimization	Yurii Nesterov, UCLouvain	None	YouTube-Lectures	2018

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💘 General Machine Learning 🌀 💥

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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	Jeffrey Miller (mathematical monk), Brown University	None	YouTube-Lectures	2011
3.	Machine Learning and Data Mining	Nando de Freitas, University of British Columbia	CPSC-340	YouTube-Lectures	2012
4.	Learning from Data	Yaser Abu-Mostafa, CalTech	CS156	YouTube-Lectures	2012
5.	Machine Learning	Rudolph Triebel, TUM	Machine Learning	YouTube-Lectures	2013
6.	Pattern Recognition	Sukhendu Das, IIT-M and C.A. Murthy, ISI-Calcutta	PR-NPTEL	YouTube-Lectures	2014
7.	Introduction to Machine Learning	Katie Malone, Sebastian Thrun, Udacity	ML-Udacity	YouTube-Lectures	2015
8.	Introduction to Machine Learning	Dhruv Batra, Virginia Tech	ECE-5984	YouTube-Lectures	2015
9.	Statistical Learning - Classification	Ali Ghodsi, University of Waterloo	STAT-441	YouTube-Lectures	2015
10	Machine Learning Theory	Shai Ben-David, University of Waterloo	None	YouTube-Lectures	2015
11.	Introduction to Machine Learning	Alex Smola, CMU	10-701	YouTube-Lectures	S2015
12.	ML: Supervised Learning	Michael Littman, Charles Isbell, Pushkar Kolhe, GaTech	ML-Udacity	YouTube-Lectures	2015
13.	ML: Unsupervised Learning	Michael Littman, Charles Isbell, Pushkar Kolhe, GaTech	ML-Udacity	YouTube-Lectures	2015
14.	Machine Learning	Pedro Domingos, UWashington	CSEP-546	YouTube-Lectures	S2016
15.	Statistical Machine Learning	Larry Wasserman, CMU	None	YouTube-Lectures	S2016
16.	Machine Learning with Large Datasets	William Cohen, CMU	10-605	YouTube-Lectures	F2016
17.	Statistical Learning - Classification	Ali Ghodsi, University of Waterloo	None	YouTube-Lectures	2017
18.	Machine Learning	Andrew Ng, Stanford University	Coursera-ML	YouTube-Lectures	2017
19.	Machine Learning	Roni Rosenfield, CMU	10-601	YouTube-Lectures	2017
20.	Statistical Machine Learning	Ryan Tibshirani, Larry Wasserman, CMU	10-702	YouTube-Lectures	S2017
21.	Machine Learning for Intelligent Systems	Kilian Weinberger, Cornell University	CS4780	YouTube-Lectures	F2018
22.	Statistical Learning Theory and Applications	Tomaso Poggio, Lorenzo Rosasco, Sasha Rakhlin	9.520/6.860	YouTube-Lectures	F2018
23.	Machine Learning and Data Mining	Mike Gelbart, University of British Columbia	CPSC-340	YouTube-Lectures	2018
24.	Foundations of Machine Learning	David Rosenberg, Bloomberg	FOML	YouTube-Lectures	2018
25.	Introduction to Machine Learning	Andreas Krause, ETH Zuerich	IntroML	YouTube-Lectures	2018
26.	Advanced Machine Learning	Joachim Buhmann, ETH Zuerich	AML-18	YouTube-Lectures	2018

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🎈 Reinforcement Learning ♨️ 🎮

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

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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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🌺 Natural Language Processing - (More Applied) 🌸 💖

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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.	Deep Learning for NLP	Min-Yen Kan, NUS	CS-6101	YouTube-Lectures	2018
7.	Neural Networks for Natural Language Processing	Graham Neubig, CMU	NN4NLP	YouTube-Lectures	2019

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🗣️ Automatic Speech Recognition 💬 💭

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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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🔥 Modern Computer Vision 📸 🎥

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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.	Multiple View Geometry (classical)	Daniel Cremers, TUM	mvg	YouTube-Lectures	2013
4.	Introduction to Computer Vision (foundation)	Aaron Bobick, Irfan Essa, Arpan Chakraborty	CV-Udacity	YouTube-Lectures	2016
5.	Autonomous Navigation for Flying Robots	Juergen Sturm, TUM	Autonavx	YouTube-Lectures	2014
6.	SLAM - Mobile Robotics	Cyrill Stachniss, Universitaet Freiburg	RobotMapping	YouTube-Lectures	2014
7.	Computational Photography	Irfan Essa, David Joyner, Arpan Chakraborty	CP-Udacity	YouTube-Lectures	2015
8.	Deep Learning for Computer Vision	UPC Barcelona	DLCV-16 DLCV-17 DLCV-18	YouTube-Lectures	2016-2018
9.	Convolutional Neural Networks	Andrew Ng, Stanford University	DeepLearning.AI	YouTube-Lectures	2017
10.	Variational Methods for Computer Vision	Daniel Cremers, TUM	VMCV	YouTube-Lectures	2017
11.	Winter School on Computer Vision	Lots of Legends, Israel Institute for Advanced Studies	WS-CV	YouTube-Lectures	2017
12.	Deep Learning for Visual Computing	Debdoot Sheet, IIT-Kgp	Nptel Notebooks	YouTube-Lectures	2018
13.	Modern Robotics	Kevin Lynch, Northwestern Robotics	modern-robot	YouTube-Lectures	2018
14.	Digial Image Processing	Alex Bronstein, Technion	CS236860	YouTube-Lectures	2018

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🌟 Boot Camps or Summer Schools 🍁

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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.	Deep Learning and Reinforcement Learning Summer School	Lots of Legends, Université de Montréal	DLRL-2017	Lecture-videos	2017
13.	Foundations of Data Science	Many Legends, Simons Institute	DS-BootCamp	YouTube-Lectures	2018
14.	Deep|Bayes	Many Legends, HSE Moscow	DeepBayes.ru	YouTube-Lectures	2018
15.	New Deep Learning Techniques	Many Legends, IPAM UCLA	IPAM-Workshop	YouTube-Lectures	2018
16.	Deep Learning and Reinforcement Learning Summer School	Lots of Legends, University of Toronto	DLRL-2018	Lecture-videos	2018
17.	Machine Learning Advances and Applications Seminar	Lots of Legends, Fields Institute, University of Toronto	MLASS	Video Lectures	2018-2019
18.	MIFODS- ML, Stats, ToC seminar	Lots of Legends, MIT	MIFODS-seminar	Lecture-videos	2018-2019

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🐦 Bird's Eye view of A(G)I 🦅

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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
3.	NYU - AI Seminars	Lots of Legends, NYU	modern-AI	YouTube-Lectures	2017-now

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To-Do 🏃

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⬜ Optimization courses which form the foundation for ML, DL, RL

⬜ Computer Vision courses which are DL & ML heavy

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

⬜ Speech recognition courses which are DL heavy

⬜ Courses on Graph Neural Networks

⬜ Section on DL/RL/ML Summer School Lectures

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Contributions 🙏

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 being optional), then please raise an issue or send a PR by updating the course according to the above format.

Danke Sehr!

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