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kmario23/deep-learning-drizzle
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
About kmario23/deep-learning-drizzle
kmario23/deep-learning-drizzle is an open-source project on GitHub, mainly written in HTML. Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!! It currently holds 12,945 stars and 0 forks with 0 open issues, and was last pushed on an unknown date (repository created unknown).
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README
: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
:heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign:| | | | ------------------------------------------------------------ | ------------------------------------------------------------ | | 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:
:heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign::heavy_minus_sign:| 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 Applicati
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