A Carnegie Mellon course on the theory underlying modern computing and data, covering the mathematical foundations later collected in the book Foundations of Data Science by Hopcroft and Kannan. Topics center on theory rather than applied machine learning.

One commenter calls it one of their favorite courses and notes it is about CS theory and mathematical foundations rather than an ML book.

What commenters said (1)

1. Strongly recommendsnilknarf2016in “Machine Learning Crash Course: Part 2”

   I 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/

   [2]https://www.cs.cornell.edu/jeh/book2016June9.pdf

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