Top 20 Math Books on Machine Learning / AI

The first 4 books (by Strang, Lang, etc) are the Masterpieces.

Linear Algebraby Strang. He writes math like few folks do, no endless paragraphs of definitions and theorems. He tells you why something is important. He wears his heart on his sleeve. If you want to spend a lifetime doing ML, sleep with this book under your pillow. Read it when you go to bed and wake up in the morning. Repeat to yourself: “eigen do it if I try.”

Strang’s MIT OpenCourse:

Introduction toApplied Mathby Strang. You’ll need to understand differential equations at some point, even to understand the dynamics of deep learning models, so you’ll benefit from Strang’s tour de force of a survey through a vast landscape of ideas, from numerical analysis to Fourier transforms.
Algebraby Lang. This legendary Yale professor has written more “yellow jacketed” tomes…