Deep Learning Drizzle:几乎所有 AI 免费课程都在这里
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:balloon::tada: Deep Learning Drizzle :confetti_ball::balloon:
Contents
-
Deep Learning (Deep Neural Networks) :arrow_heading_down:
-
Machine Learning Fundamentals :arrow_heading_down:
-
Optimization for Machine Learning :arrow_heading_down:
-
General Machine Learning :arrow_heading_down:
-
Reinforcement Learning :arrow_heading_down:
-
Probabilistic Graphical Models :arrow_heading_down:
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Natural Language Processing :arrow_heading_down:
-
Automatic Speech Recognition :arrow_heading_down:
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Modern Computer Vision :arrow_heading_down:
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Boot Camps or Summer Schools :arrow_heading_down:
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Bird's Eye view of Artificial (General) Intelligence :arrow_heading_down:
: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 CS231nNone
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
Go to Contents :arrow_heading_up:
: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 GrinfeldNone
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
Go to Contents :arrow_heading_up:
: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 UniversityNone
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
Go to Contents :arrow_heading_up:
: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 WaterlooNone
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
Go to Contents :arrow_heading_up:
: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, UMichiganNone
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
Go to Contents :arrow_heading_up:
: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 AustriaNone
YouTube-Lectures
2016
5.
Probabilistic Graphical Models
Nicholas Zabaras, University of Notre Dame
PGM
YouTube-Lectures
2018
Go to Contents :arrow_heading_up:
: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 2019Go to Contents :arrow_heading_up:
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, AoENone
YouTube-Videos
2015-2018
Go to Contents :arrow_heading_up:
: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 2018Go to Contents :arrow_heading_up:
: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-ResearchNone
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
Go to Contents :arrow_heading_up:
: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 2018-2019Go to Contents :arrow_heading_up:
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
Go to Contents :arrow_heading_up:
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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