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Besides the DL book, there's other excellent texts that are freely available/open content on the web: - Elements statistical Learning, Hastie et al - Shalev-S
by gtani 10y ago
Besides the DL book, there's other excellent texts that are freely available/open content on the web:
- Elements statistical Learning, Hastie et al
- Shalev-Shwartz and Ben-David: http://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/understanding-machine-learning-theory-algorithms.pdf http://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning...
- the late David MacKay's Info Theory
- Bayesian Reasoning in ML, Barber
- Hopcroft/Kannan (this is an older version, you can google latest: http://www.cs.cornell.edu/jeh/book112013.pdf http://www.cs.cornell.edu/jeh/book112013.pdf
- nilknarf 10y agoI didn't expect to see Hopcroft/Kannan in that list. I used it in a course taught by Kannan and back then it was called "Computer Science Theory for the Information Age". Apparently the book is now called "Foundations of Data Science". I always thought the old naming was terrible but compared to the new title it actually describes the content a lot better since the book is mainly about CS theory and mathematical foundations for them. It was one of my favorite courses but I would not classify it as ML book. [1]https://www.cs.cmu.edu/~venkatg/teaching/CStheory-infoage/ https://www.cs.cmu.edu/~venkatg/teaching/CStheory-infoage/ [2]https://www.cs.cornell.edu/jeh/book2016June9.pdf https://www.cs.cornell.edu/jeh/book2016June9.pdf