As a computer science graduate involved in academic research with plans to continue an academic career, i feel like i lack of strong mathematical background to be at satisfying level and competitive among quality computer scientists. My interests include AI (including Machine Learning), Computer Vision and everything it includes, optimization problems. I would like to get an advice about the quality books for Linear Algebra, Discrete Math, Probability and Statistics, Numerical analysis, and everything you need is necessary for a good theoretical understanding of the previously mentioned computer science fields.
2026-04-04 15:13:34.1775315614
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Computer Science - Mathematical Foundation
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For self study in probability and statistics, you might look at Wackerly, Mendenhall, Schaffer. I have used it for calculus-prerequisite undergraduate courses many times. Older editions are available at reasonable prices, and you might be able to find a student answer guide that matches the same edition.
There are many other excellent books, but I am focusing a book for self study by someone with CS background and interests. (Also, the probability book by Grinsted and Snell has a lot of interesting examples, and an author-authorized .pdf of it is available free online.)
Linear Algebra covered by James Carrell covers the fundamental concepts of Linear Algebra important to all branches of mathematics. I like it because it is written to be readable by undergraduates and it is available in .pdf format