Mathematics for Machine Learning by Deisenroth, Faisal, Ong (2020) — Unified LA + multivariate calc + probability for ML-minded people. PDF
Linear Algebra by Jim Hefferon (various) — Clear, concept-first linear algebra without mysticism. PDF
Linear Algebra Done Right by Sheldon Axler (2024) — Determinant-free approach to LA that builds real intuition. PDF
Elementary Differential Equations by William F. Trench (2013+) — A full ODE treatment including BVPs and series methods. Online
Book of Proof by Richard Hammack (2018) — Bridge from computation to proof. Sets, logic, induction, functions. PDF
Concrete Mathematics by Graham, Knuth, Patashnik (1994) — The discrete math you actually need. Sums, recurrences, number theory. (copyrighted)
Calculus Made Easy by Silvanus P. Thompson (1914) — Still the gentlest and most irreverent intro to calculus ever written. PDF
Naive Set Theory by Paul Halmos (1960) — Bite-sized set theory for working mathematicians. Deceptively deep. (copyrighted)
The Princeton Companion to Mathematics by Timothy Gowers (ed.) (2008) — 1000+ pages surveying all of modern mathematics. The map of math. (copyrighted)
Introduction to Probability by Blitzstein & Hwang (2019) — Best modern probability textbook. Stat 110 at Harvard. (copyrighted)