├── LICENSE └── README.md /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2020 brpy 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # ml-books 2 | A list of freely available Machine Learning, Data Science and Statistics books. 3 | 4 | | Book/Resource| Author(s) | Links|:arrow_double_down:| 5 | |-----------|----------------------------|-----------------------------------------------|---| 6 | | d2l-ai| Community | [[github]](https://github.com/d2l-ai/d2l-en) [[pdf]](https://d2l.ai/d2l-en.pdf)|:heavy_check_mark:| 7 | | Data Science Handbook| Jake Vanderplas | [[github]](https://github.com/jakevdp/PythonDataScienceHandbook) [[online]](https://jakevdp.github.io/PythonDataScienceHandbook/)|:x:| 8 | | Deep Learning Book| Ian Goodfellow, Yoshua Bengio, Aaron Courville | [[online]](https://www.deeplearningbook.org/)|:x:| 9 | | Deep Learning with Pytorch|Eli Stevens, Luca Antiga, Thomas Viehmann| [[pdf]](https://pytorch.org/assets/deep-learning/Deep-Learning-with-PyTorch.pdf)|:heavy_check_mark:| 10 | | Introdution to Probability| Jessica Hwang and Joseph K. Blitzstein | [[Google Drive]](https://drive.google.com/file/d/1VmkAAGOYCTORq1wxSQqy255qLJjTNvBI/view)|:x:| 11 | |Ml Primer|Mihail Eric| [[pdf]](https://www.confetti.ai/assets/ml-primer/ml_primer.pdf) |:heavy_check_mark:| 12 | |Mathematics For Machine Learning|Marc Peter Deisenroth, A Aldo Faisal, and Cheng Soon Ong|[[github]](https://github.com/mml-book/mml-book.github.io) [[pdf]](https://mml-book.github.io/book/mml-book.pdf)|:heavy_check_mark:| 13 | |Foundations of Data Science|Avrim Blum, John Hopcroft, Ravindran Kannan| [[pdf]](https://www.cs.cornell.edu/jeh/book.pdf)|:heavy_check_mark:| 14 | |Think Stats|Allen Downey|[[github]](https://github.com/AllenDowney/ThinkStats2) [[pdf]](https://greenteapress.com/thinkstats/thinkstats.pdf)|:heavy_check_mark:| 15 | |Math4ml|Garrett Thomas|[[github]](https://github.com/gwthomas/math4ml) [[pdf]](https://gwthomas.github.io/docs/math4ml.pdf)|:heavy_check_mark:| 16 | |Think bayes|Allen Downey|[[github]](https://github.com/AllenDowney/ThinkBayes) [[html]](http://www.greenteapress.com/thinkbayes/html/index.html) [[pdf]](http://www.greenteapress.com/thinkbayes/thinkbayes.pdf)|:heavy_check_mark:| 17 | |Think python 2|Allen Downey|[[pdf]](http://greenteapress.com/thinkpython2/thinkpython2.pdf)|:heavy_check_mark:| 18 | |Intermediate python|Muhammad Yasoob Ullah Khalid|[[pdf]](https://buildmedia.readthedocs.org/media/pdf/intermediatepythongithubio/latest/intermediatepythongithubio.pdf)|:heavy_check_mark:| 19 | |Pattern Recognition and Machine Learning|Christopher Bishop|[[pdf]](https://www.microsoft.com/en-us/research/uploads/prod/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf)|:heavy_check_mark:| 20 | |Computer Age Statistical Inference|Bradley Efron, Trevor Hastie|[[pdf]](https://web.stanford.edu/~hastie/CASI_files/PDF/casi.pdf)|:heavy_check_mark:| 21 | |An Introduction to Statistical Learning|Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani|[[pdf]](https://statlearning.com/ISLR%20Seventh%20Printing.pdf)|:heavy_check_mark:| 22 | |The Elements ofStatistical Learning|Trevor Hastie, Robert Tibshirani, Jerome Friedman|[[pdf]](https://web.stanford.edu/~hastie/Papers/ESLII.pdf)|:heavy_check_mark:| 23 | --------------------------------------------------------------------------------