Pretty soon I will be finishing up Understanding Machine Learning: From Theory to Algorithms by Shai Ben-David and Shai Shalev-Shwartz. I absolutely love the subject and want to learn more, the only issue is I'm having trouble finding a book that could come after this. Ultimately, my goal is to read papers in JMLR's COLT.

  1. Is there a book similar to "Understanding Machine Learning: From Theory to Algorithms" that would progress my knowledge further and would go well after reading UML?

  2. Is there any other materials (not a book) that could allow me to learn more or prepare me for reading a journal like the one mentioned above?

(Also, taking courses in this is not really an option, so this will be for self-study).

(Note that I have also asked this question here on TCS SE, but it was recommended I also ask here.)


1 Answer 1


Although I have only partially read or not read at all some of the following resources and some of these resources may not cover more advanced topics than the ones presented in the book you are reading, I think they can still be useful for your purposes, so I will share them with you.

I would also like to note that if you understand the contents of the book you are currently reading, you are probably already prepared for reading some (if not most of) the research papers you wish to read. Initially, you may find them a little bit too succinct and sometimes unclear or complex, but you need to get used to this format, so there's nothing stopping you from trying to read them and learn even more by doing this exercise.



Courses (videos)

Lecture notes


See also this list of resources https://kiranvodrahalli.github.io/links/#resources-notes-textbooks-monographs-classes-etc compiled by Kiran Vodrahalli.

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    Commented Jan 16, 2021 at 19:41

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