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@ -5,8 +5,8 @@ The following is a list of free and/or open source books on machine learning, st
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* [Distributed Machine Learning Patterns](https://github.com/terrytangyuan/distributed-ml-patterns) - Book (free to read online) + Code
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* [The Hundred-Page Machine Learning Book](http://themlbook.com/wiki/doku.php)
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* [Real World Machine Learning](https://www.manning.com/books/real-world-machine-learning) [Free Chapters]
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* [An Introduction To Statistical Learning With Applications In R](https://hastie.su.domains/ISLR2/ISLRv2_corrected_June_2023.pdf) - Book + R Code
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* [An Introduction To Statistical Learning With Applications In Python](https://hastie.su.domains/ISLP/ISLP_website.pdf) - Book + Python Code
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* [An Introduction To Statistical Learning With Applications In R](https://drive.usercontent.google.com/download?id=106d-rN7cXpyAkgrUqjcPONNCyO-rX7MQ&export=download) - Book + R Code
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* [An Introduction To Statistical Learning With Applications In Python](https://drive.usercontent.google.com/download?id=1ajFkHO6zjrdGNqhqW1jKBZdiNGh_8YQ1&export=download) - Book + Python Code
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* [Elements of Statistical Learning](https://web.stanford.edu/~hastie/ElemStatLearn/) - Book
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* [Computer Age Statistical Inference (CASI)](https://web.stanford.edu/~hastie/CASI_files/PDF/casi.pdf) ([Permalink as of October 2017](https://perma.cc/J8JG-ZVFW)) - Book
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* [Probabilistic Programming & Bayesian Methods for Hackers](http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/) - Book + IPython Notebooks
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