├── .github └── ISSUE_TEMPLATE │ └── add-lecture-notes.md ├── LICENSE.md └── README.md /.github/ISSUE_TEMPLATE/add-lecture-notes.md: -------------------------------------------------------------------------------- 1 | --- 2 | name: Add Lecture Notes 3 | about: Add Lecture Notes 4 | title: 'Lecture name [WIP] ' 5 | labels: wip 6 | assignees: '' 7 | 8 | --- 9 | 10 | Lecture: 11 | Notes by: 12 | Video lecture: 13 | -------------------------------------------------------------------------------- /LICENSE.md: -------------------------------------------------------------------------------- 1 | The notes are licensed under the Attribution-NonCommercial-ShareAlike 4.0 International. 2 | 3 | This is a human-readable summary of (and not a substitute for) the [license](https://creativecommons.org/licenses/by-nc-sa/4.0/). 4 | 5 | You are free to: 6 | * Share — copy and redistribute the material in any medium or format 7 | * Adapt — remix, transform, and build upon the material 8 | The licensor cannot revoke these freedoms as long as you follow the license terms. 9 | 10 | Under the following terms: 11 | * Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. 12 | * Noncommercial — You may not use the material for commercial purposes. 13 | * Share Alike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original. 14 | 15 | No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits. 16 | 17 | Notices: 18 | You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation. 19 | 20 | No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material. 21 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # 🎓 Machine Learning Course Notes 2 | A place to collaborate and share lecture notes on all topics related to machine learning, NLP, and AI. 3 | 4 | `WIP` denotes work in progress. 5 | 6 | --- 7 | 8 | ### Machine Learning Specialization (2022) 9 | [Website](https://www.coursera.org/specializations/machine-learning-introduction) | Instructor: Andrew Ng 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 |
LectureDescriptionVideoNotesAuthor
Introduction to Machine LearningSupervised Machine Learning: Regression and ClassificationVideosNotesElvis
Advanced Learning AlgorithmsAdvanced Learning AlgorithmsVideosWIPElvis
Unsupervised Learning, Recommenders, Reinforcement LearningUnsupervised Learning, Recommenders, Reinforcement LearningVideosWIPElvis
42 | 43 | --- 44 | 45 | ### MIT 6.S191 Introduction to Deep Learning (2022) 46 | [Website](http://introtodeeplearning.com/) | Lectures by: Alexander Amini and Ava Soleimany 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | 70 | 71 | 72 | 73 | 74 | 75 | 76 | 77 | 78 | 79 | 80 | 81 | 82 | 83 | 84 | 85 | 86 | 87 | 88 | 89 | 90 | 91 | 92 | 93 |
LectureDescriptionVideoNotesAuthor
Introduction to Deep LearningBasic fundamentals of neural networks and deep learning.VideoNotesElvis
RNNs and TransformersIntroduction to recurrent neural networks and transformers.VideoNotesElvis
Deep Computer VisionDeep Neural Networks for Computer Vision.VideoNotesElvis
Deep Generative ModelingAutoencoders and GANs.VideoNotesElvis
Deep Reinforcement LearningDeep RL key concepts and DQNs.VideoNotesElvis
94 | 95 | --- 96 | 97 | ### CMU Neural Nets for NLP (2021) 98 | [Website](http://phontron.com/class/nn4nlp2021/schedule.html) | Instructor: Graham Neubig 99 | 100 | 101 | 102 | 103 | 104 | 105 | 106 | 107 | 108 | 109 | 110 | 111 | 112 | 113 | 114 | 115 | 116 |
LectureDescriptionVideoNotesAuthor
Introduction to Simple Neural Networks for NLPProvides an introduction to neural networks for NLP covering concepts like BOW, CBOW, and Deep CBOWVideoNotesElvis
117 | 118 | --- 119 | 120 | ### CS224N: Natural Language Processing with Deep Learning (2022) 121 | [Website](https://www.youtube.com/playlist?list=PLoROMvodv4rOSH4v6133s9LFPRHjEmbmJ) | Instructor: C‪hristopher Manning 122 | 123 | 124 | 125 | 126 | 127 | 128 | 129 | 130 | 131 | 132 | 133 | 134 | 135 | 136 | 137 | 138 | 139 | 140 | 141 | 142 | 143 | 144 | 145 | 146 |
LectureDescriptionVideoNotesAuthor
Introduction and Word VectorsIntroduction to NLP and Word Vectors.VideoNotesElvis
Neural ClassifiersNeural Classifiers for NLP.VideoWIPElvis
147 | 148 | --- 149 | 150 | ### CS25: Transformers United 151 | [Website](https://web.stanford.edu/class/cs25/) | Instructors: Div Garg, Chetanya Rastogi, Advay Pal 152 | 153 | 154 | 155 | 156 | 157 | 158 | 159 | 160 | 161 | 162 | 163 | 164 | 165 | 166 | 167 | 168 | 169 | 170 | 171 | 172 | 173 | 174 | 175 | 176 |
LectureDescriptionVideoNotesAuthor
Introduction to TransformersA short summary of attention and Transformers.VideoNotesElvis
Transformers in Language: GPT-3, CodexThe development of GPT Models including GPT3.VideoWIPElvis
177 | 178 | --- 179 | 180 | ### Neural Networks: Zero to Hero 181 | [Lectures](https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ) | Instructors: Andrej Karpathy 182 | 183 | 184 | 185 | 186 | 187 | 188 | 189 | 190 | 191 | 192 | 193 | 194 | 195 | 196 | 197 | 198 | 199 |
LectureDescriptionVideoNotesAuthor
Let's build GPT: from scratch, in code, spelled outDetailed walkthrough of GPTVideoWIPElvis
200 | 201 | --- 202 | 203 | ### Miscellaneous Lectures 204 | 205 | 206 | 207 | 208 | 209 | 210 | 211 | 212 | 213 | 214 | 215 | 216 | 217 | 218 | 219 | 220 | 221 | 222 | 223 | 224 | 225 | 226 | 227 | 228 |
LectureDescriptionVideoNotesAuthor
Introduction to Diffusion ModelsTechnical overview of Diffusion ModelsVideoWIPElvis
Reinforcement Learning from Human Feedback (RLHF)Overview of RLHFVideoWIPElvis
229 | 230 | 231 | --- 232 | ### How To Contribute 233 | 234 | 1) Identify a course and lecture from this [list](https://github.com/dair-ai/ML-YouTube-Courses). If you are working on notes for a lecture, please indicate by opening an issue. This avoids duplicate work. 235 | 2) Write your notes, preferably in a Google document, Notion document, or GitHub repo. 236 | 3) We care about quality, so make sure to revise your notes before submitting. 237 | 4) Once you are finished, open a PR here. 238 | 239 | 240 | If you have any questions, open an issue or reach out to me on [Twitter](https://twitter.com/omarsar0). 241 | 242 | Join our [Discord](https://discord.gg/FzNtjEK9dg). 243 | --------------------------------------------------------------------------------