deep-learning-drizzle

kmario23 / deep-learning-drizzle

汇集深度学习、强化学习、机器学习、计算机视觉和NLP领域的顶尖公开课视频，助你通过系统学习掌握AI核心知识。

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:balloon: :tada: Deep Learning Drizzle :confetti_ball: :balloon:

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

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Contents

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Deep Learning (Deep Neural Networks) :arrow_heading_down: Probabilistic Graphical Models :arrow_heading_down:
Machine Learning Fundamentals :arrow_heading_down: Natural Language Processing :arrow_heading_down:
Optimization for Machine Learning :arrow_heading_down: Automatic Speech Recognition :arrow_heading_down:
General Machine Learning :arrow_heading_down: Modern Computer Vision :arrow_heading_down:
Reinforcement Learning :arrow_heading_down: Boot Camps or Summer Schools :arrow_heading_down:
Bayesian Deep Learning :arrow_heading_down: Medical Imaging :arrow_heading_down:
Graph Neural Networks :arrow_heading_down: Bird's-eye view of Artificial Intelligence :arrow_heading_down:

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:tada: Deep Learning (Deep Neural Networks) :confetti_ball: :balloon:

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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. Deep Learning for Perception Dhruv Batra, Virginia Tech ECE-6504 YouTube-Lectures 2015
5. Deep Learning Ali Ghodsi, University of Waterloo STAT-946 YouTube-Lectures F2015
6. CS231n: CNNs for Visual Recognition Andrej Karpathy, Stanford University CS231n None 2015
7. CS224d: Deep Learning for NLP Richard Socher, Stanford University CS224d YouTube-Lectures 2015
8. Bay Area Deep Learning Many legends, Stanford None YouTube-Lectures 2016
9. CS231n: CNNs for Visual Recognition Andrej Karpathy, Stanford University CS231n YouTube-Lectures
(Academic Torrent)		 2016
10. Neural Networks Hugo Larochelle, Université de Sherbrooke Neural-Networks YouTube-Lectures
(Academic Torrent)		 2016
11. CS224d: Deep Learning for NLP Richard Socher, Stanford University CS224d YouTube-Lectures
(Academic Torrent)		 2016
12. CS224n: NLP with Deep Learning Richard Socher, Stanford University CS224n YouTube-Lectures 2017
13. CS231n: CNNs for Visual Recognition Justin Johnson, Stanford University CS231n YouTube-Lectures
(Academic Torrent)		 2017
14. Topics in Deep Learning Ruslan Salakhutdinov, CMU 10707 YouTube-Lectures F2017
15. Deep Learning Crash Course Leo Isikdogan, UT Austin None YouTube-Lectures 2017
16. Deep Learning and its Applications François Pitié, Trinity College Dublin EE4C16 YouTube-Lectures 2017
17. Deep Learning Andrew Ng, Stanford University CS230 YouTube-Lectures 2018
18. UvA Deep Learning Efstratios Gavves, University of Amsterdam UvA-DLC Lecture-Videos 2018
19. Advanced Deep Learning and Reinforcement Learning Many legends, DeepMind None YouTube-Lectures 2018
20. Machine Learning Peter Bloem, Vrije Universiteit Amsterdam MLVU YouTube-Lectures 2018
21. Deep Learning Francois Fleuret, EPFL EE-59 Video-Lectures 2018
22. Introduction to Deep Learning Alexander Amini, Harini Suresh and others, MIT 6.S191 YouTube-Lectures
2017-version		 2017- 2021
23. Deep Learning for Self-Driving Cars Lex Fridman, MIT 6.S094 YouTube-Lectures 2017-2018
24. Introduction to Deep Learning Bhiksha Raj and many others, CMU 11-485/785 YouTube-Lectures S2018
25. Introduction to Deep Learning Bhiksha Raj and many others, CMU 11-485/785 YouTube-Lectures Recitation-Inclusive F2018
26. Deep Learning Specialization Andrew Ng, Stanford DL.AI YouTube-Lectures 2017-2018
27. Deep Learning Ali Ghodsi, University of Waterloo STAT-946 YouTube-Lectures F2017
28. Deep Learning Mitesh Khapra, IIT-Madras CS7015 YouTube-Lectures 2018
29. Deep Learning for AI UPC Barcelona DLAI-2017
DLAI-2018		 YouTube-Lectures 2017-2018
30. Deep Learning Alex Bronstein and Avi Mendelson, Technion CS236605 YouTube-Lectures 2018
31. MIT Deep Learning Many Researchers, Lex Fridman, MIT 6.S094, 6.S091, 6.S093 YouTube-Lectures 2019
32. Deep Learning Book companion videos Ian Goodfellow and others DL-book slides YouTube-Lectures 2017
33. Theories of Deep Learning Many Legends, Stanford Stats-385 YouTube-Lectures
(first 10 lectures)		 F2017
34. Neural Networks Grant Sanderson None YouTube-Lectures 2017-2018
35. CS230: Deep Learning Andrew Ng, Kian Katanforoosh, Stanford CS230 YouTube-Lectures A2018
36. Theory of Deep Learning Lots of Legends, Canary Islands DALI'18 YouTube-Lectures 2018
37. Introduction to Deep Learning Alex Smola, UC Berkeley Stat-157 YouTube-Lectures S2019
38. Deep Unsupervised Learning Pieter Abbeel, UC Berkeley CS294-158 YouTube-Lectures S2019
39. Machine Learning Peter Bloem, Vrije Universiteit Amsterdam MLVU YouTube-Lectures 2019
40. Deep Learning on Computational Accelerators Alex Bronstein and Avi Mendelson, Technion CS236605 YouTube-Lectures S2019
41. Introduction to Deep Learning Bhiksha Raj and many others, CMU 11-785 YouTube-Lectures S2019
42. Introduction to Deep Learning Bhiksha Raj and many others, CMU 11-785 YouTube-Lectures
Recitations		 F2019
43. UvA Deep Learning Efstratios Gavves, University of Amsterdam UvA-DLC Lecture-Videos S2019
44. Deep Learning Prabir Kumar Biswas, IIT Kgp None YouTube-Lectures 2019
45. Deep Learning and its Applications Aditya Nigam, IIT Mandi CS-671 YouTube-Lectures 2019
46. Neural Networks Neil Rhodes, Harvey Mudd College CS-152 YouTube-Lectures F2019
47. Deep Learning Thomas Hofmann, ETH Zürich DAL-DL Lecture-Videos F2019
48. Deep Learning Milan Straka, Charles University NPFL114 Lecture-Videos S2019
49. UvA Deep Learning Efstratios Gavves, University of Amsterdam UvA-DLC-19 Lecture-Videos F2019
50. Artificial Intelligence: Principles and Techniques Percy Liang and Dorsa Sadigh, Stanford University CS221 YouTube-Lectures F2019
51. Analyses of Deep Learning Lots of Legends, Stanford University STATS-385 YouTube-Lectures 2017-2019
52. Deep Learning Foundations and Applications Debdoot Sheet and Sudeshna Sarkar, IIT-Kgp AI61002 YouTube-Lectures S2020
53. Designing, Visualizing, and Understanding Deep Neural Networks John Canny, UC Berkeley CS 182/282A YouTube-Lectures S2020
54. Deep Learning Yann LeCun and Alfredo Canziani, NYU DS-GA 1008 YouTube-Lectures S2020
55. Introduction to Deep Learning Bhiksha Raj, CMU 11-785 YouTube-Lectures S2020
56. Deep Unsupervised Learning Pieter Abbeel, UC Berkeley CS294-158 YouTube-Lectures S2020
57. Machine Learning Peter Bloem, Vrije Universiteit Amsterdam VUML YouTube-Lectures S2020
58. Deep Learning (with PyTorch) Alfredo Canziani and Yann LeCun, NYU DS-GA 1008 YouTube-Lectures S2020
59. Introduction to Deep Learning and Generative Models Sebastian Raschka, UW-Madison Stat453 YouTube-Lectures S2020
60. Deep Learning Andreas Maier, FAU Erlangen-Nürnberg DL-2020 YouTube-Lectures
Lecture-Videos		 SS2020
61. Introduction to Deep Learning Laura Leal-Taixé and Matthias Niessner, TU-München I2DL-IN2346 YouTube-Lectures SS2020
62. Deep Learning Sargur Srihari, SUNY-Buffalo CSE676 YouTube-Lectures-P1
YouTube-Lectures-P2		 2020
63. Deep Learning Lecture Series Lots of Legends, DeepMind x UCL, London DLLS-20 YouTube-Lectures 2020
64. MultiModal Machine Learning Louis-Philippe Morency & others, Carnegie Mellon University 11-777 MMML-20 YouTube-Lectures F2020
65. Reliable and Interpretable Artificial Intelligence Martin Vechev, ETH Zürich RIAI-20 YouTube-Lectures F2020
66. Fundamentals of Deep Learning David McAllester, Toyota Technological Institute, Chicago TTIC-31230 YouTube-Lectures F2020
67. Foundations of Deep Learning Soheil Feize, University of Maryland, College Park CMSC 828W YouTube-Lectures F2020
68. Deep Learning Andreas Geiger, Universität Tübingen DL-UT YouTube-Lectures W20/21
69. Deep Learning Andreas Maier, FAU Erlangen-Nürnberg DL-FAU YouTube-Lectures W20/21
70. Fundamentals of Deep Learning Terence Parr and Yannet Interian, University of San Francisco DL-Fundamentals YouTube-Lectures S2021
71. Full Stack Deep Learning Pieter Abbeel, Sergey Karayev, UC Berkeley FS-DL YouTube-Lectures S2021
72. Deep Learning: Designing, Visualizing, and Understanding DNNs Sergey Levine, UC Berkeley CS 182 YouTube-Lectures S2021
73. Deep Learning in the Life Sciences Manolis Kellis, MIT 6.874 YouTube-Lectures S2021
74. Introduction to Deep Learning and Generative Models Sebastian Raschka, University of Wisconsin-Madison Stat 453 YouTube-Lectures S2021
75. Deep Learning Alfredo Canziani and Yann LeCun, NYU NYU-DLSP21 YouTube-Lectures S2021
76. Applied Deep Learning Alexander Pacha, TU Wien None YouTube-Lectures 2020-2021
77. Machine Learning Hung-yi Lee, National Taiwan University ML'21 YouTube-Lectures S2021
78. Mathematics of Deep Learning Lots of legends, FAU MoDL Lecture-Videos 2019-21
79. Deep Learning Peter Bloem, Michael Cochez, and Jakub Tomczak, VU-Amsterdam DL YouTube-Lectures 2020-21
80. Applied Deep Learning Maziar Raissi, UC Boulder ADL'21 YouTube-Lectures 2021
81. An Introduction to Group Equivariant Deep Learning Erik J. Bekkers, Universiteit van Amsterdam UvAGEDL YouTube-Lectures 2022

Go to Contents :arrow_heading_up:

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

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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, Brown University mathematical monk YouTube-Lectures 2011
3. Information Theory, Pattern Recognition, and Neural Networks David Mackay, University of Cambridge ITPRNN YouTube-Lectures 2012
4. Linear Algebra Review Zico Kolter, CMU LinAlg YouTube-Lectures 2013
5. Probability and Statistics Michel van Biezen None YouTube-Lectures 2015
6. Linear Algebra: An in-depth Introduction Pavel Grinfeld None Part-1
Part-2
Part-3
Part-4		 2015- 2017
7. Multivariable Calculus Grant Sanderson, Khan Academy None YouTube-Lectures 2016
8. Essence of Linear Algebra Grant Sanderson None YouTube-Lectures 2016
9. Essence of Calculus Grant Sanderson None YouTube-Lectures 2017-2018
10. Math Background for Machine Learning Geoff Gordon, CMU 10-606, 10-607 YouTube-Lectures F2017
11. Mathematics for Machine Learning (Linear Algebra, Calculus) David Dye, Samuel Cooper, and Freddie Page, IC-London MML YouTube-Lectures 2018
12. Multivariable Calculus S.K. Gupta and Sanjeev Kumar, IIT-Roorkee MVC YouTube-Lectures 2018
13. Engineering Probability Rich Radke, Rensselaer Polytechnic Institute None YouTube-Lectures 2018
14. Matrix Methods in Data Analysis, Signal Processing, and Machine Learning Gilbert Strang, MIT 18.065 YouTube-Lectures S2018
15. Information Theory Himanshu Tyagi, IISC, Bengaluru E2 201 YouTube-Lectures 2018-20
16. Math Camp Mark Walker, University of Arizona UAMathCamp / Econ-519 YouTube-Lectures 2019
17. A 2020 Vision of Linear Algebra Gilbert Strang, MIT VoLA YouTube-Lectures S2020
18. Mathematics for Numerical Computing and Machine Learning Szymon Rusinkiewicz, Princeton University COS-302 YouTube-Lectures F2020
19. Essential Statistics for Neuroscientists Philipp Berens, Universität Klinikum Tübingen None YouTube-Lectures 2020
20. Mathematics for Machine Learning Ulrike von Luxburg, Eberhard Karls Universität Tübingen Math4ML YouTube-Lectures W2020
21. Introduction to Causal Inference Brady Neal, Mila, Montréal CausalInf YouTube-Lectures F2020
22. Applied Linear Algebra Andrew Thangaraj, IIT Madras EE5120 YouTube-Lectures 2021
23. Mathematical Tools for Data Science Carlos Fernandez-Granda, New York University DS-GA 1013/Math-GA 2824 YouTube-Lectures 2021
24. Mathematics for Numerical Computing and Machine Learning Ryan Adams, Princeton University COS 302 / SML 305 YouTube-Lectures 2021

Go to Contents :arrow_heading_up:

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

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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. Introduction to Optimization Michael Zibulevsky, Technion CS-236330 YouTube-Lectures 2009
3. Optimization for Machine Learning S V N Vishwanathan, Purdue University None YouTube-Lectures 2011
4. Optimization Geoff Gordon & Ryan Tibshirani, CMU 10-725 YouTube-Lectures 2012
5. Convex Optimization Joydeep Dutta, IIT-Kanpur cvx-nptel YouTube-Lectures 2013
6. Foundations of Optimization Joydeep Dutta, IIT-Kanpur fop-nptel YouTube-Lectures 2014
7. Algorithmic Aspects of Machine Learning Ankur Moitra, MIT 18.409-AAML YouTube-Lectures S2015
8. Numerical Optimization Shirish K. Shevade, IISC None YouTube-Lectures 2015
9. Convex Optimization Ryan Tibshirani, CMU 10-725 YouTube-Lectures S2015
10. Convex Optimization Ryan Tibshirani, CMU 10-725 YouTube-Lectures F2015
11. Advanced Algorithms Ankur Moitra, MIT 6.854-AA YouTube-Lectures S2016
12. Introduction to Optimization Michael Zibulevsky, Technion None YouTube-Lectures 2016
13. Convex Optimization Javier Peña & Ryan Tibshirani 10-725/36-725 YouTube-Lectures F2016
14. Convex Optimization Ryan Tibshirani, CMU 10-725 YouTube-Lectures
Lecture-Videos		 F2018
15. Modern Algorithmic Optimization Yurii Nesterov, UCLouvain None YouTube-Lectures 2018
16. Optimization, Foundations of Optimization Mark Walker, University of Arizona MathCamp-20 YouTube-Lectures-Found.
YouTube-Lectures-Opt		 2019 - now
17. Optimization: Principles and Algorithms Michel

README 内容较长，此处已截断，完整内容请查看 GitHub 仓库。

文档抓取自 GitHub 仓库 README，版权归原作者所有；已过滤徽章等噪音并经安全消毒后展示。