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 * [Mathematics for Machine Learning](https://mml-book.github.io) - Marc Peter Deisenroth, A Aldo Faisal, and Cheng Soon Ong
 * [Neural Networks and Deep Learning](http://neuralnetworksanddeeplearning.com)
 * [Probabilistic Models in the Study of Language](http://idiom.ucsd.edu/~rlevy/pmsl_textbook/text.html) (Draft, with R code)
+* [Python Machine Learning Projects](https://www.digitalocean.com/community/books/python-machine-learning-projects-a-digitalocean-ebook) - Lisa Tagliaferri and Brian Boucheron (PDF, EPUB, MOBI)
 * [Reinforcement Learning: An Introduction](http://incompleteideas.net/book/RLbook2020.pdf) - Richard S. Sutton, Andrew G. Barto (PDF)
 * [Speech and Language Processing (3rd Edition Draft)](https://web.stanford.edu/~jurafsky/slp3/ed3book.pdf) - Daniel Jurafsky, James H. Martin (PDF)
 * [The Elements of Statistical Learning](https://web.stanford.edu/~hastie/ElemStatLearn/) - Trevor Hastie, Robert Tibshirani, and Jerome Friedman