Course textbook and companion reader
The Foundations of Math for Machine Learning
Two books, and four ways in.
The course textbook and its history companion, each free to read in a browser and free on Apple Books.
Course Textbook
The Foundations of Math for Machine Learning
Discrete Math and Linear Algebra starts with counting the ways something can happen and ends with a matrix that predicts where a system settles. Four units: Intro to Probability, (Not So Simple) Probability, Matrix Theory, and Markov Chains.
Companion Reader
The Math Behind Machine Learning, Twenty-Five Centuries in the Making
Pingala was counting the rhythms of Sanskrit poetry. Cardano was trying to win at dice. A clerk in Han China was dividing up bundles of rice on a ruled board and doing Gaussian elimination two thousand years before it had that name. This is where the mathematics behind machine learning actually came from.
The rest of the shelf
Every one of them is free, opens in a browser, and keeps working with the wifi off.
