SK

Textbooks on Various Subjects

Date written Jun 7, 2020
Date updated Last updated: Nov 10, 2020
Filed under Books in ref

Contents

Well-written textbooks (or even theses) are the fastest way to learn technical topics that have achieved critical mass. Inspired by a similarly titled post on LessWrong, I have my own evolving list.

For obvious reasons, I have not read most books cover to cover. I have, however, read a few chapters of each to be convinced that the rest of the book would be worth reading. Often, multiple books cater to overlapping topics, and provide complementary strengths to aid understanding. When multiple books are specified within each (sub-)section, it is safe to assume that as a "soft" recommendation order.

General Mathematics

Linear Algebra

Numerical Methods

Optimization

Differential Equations

Machine Learning / Statistics

Bayesian Inference

Gaussian Processes

Deep Learning

  • Deep Learning by Ian Goodfellow and Yoshua Bengio and Aaron Courville (2016)

Reinforcement Learning

Learning Theory

Monte Carlo Methods