Sridhar Mahadevan's 20 math books for Machine Learning

1.
Introduction to Linear Algebra
Introduction to Linear Algebra 4.24 avg rating — 689 ratings
3.
Convex Optimization
Convex Optimization 4.48 avg rating — 343 ratings
4.
Optimization by Vector Space Methods
Optimization by Vector Space Methods 4.51 avg rating — 37 ratings
5.
Causal Inference in Statistics: A Primer
Causal Inference in Statistics: A Primer 4.10 avg rating — 244 ratings
7.
Linear Statistical Inference and its Applications
Linear Statistical Inference and its Applications really liked it 4.00 avg rating — 7 ratings
8.
Convex Analysis
Convex Analysis 4.44 avg rating — 27 ratings
10.
Introduction to Applied Mathematics
Introduction to Applied Mathematics 4.02 avg rating — 55 ratings
14.
Algebra (Graduate Texts in Mathematics, 211)
Algebra (Graduate Texts in Mathematics, 211) 4.10 avg rating — 211 ratings
15.
Introduction to Topological Manifolds
Introduction to Topological Manifolds 4.53 avg rating — 64 ratings
16.
Introduction to Smooth Manifolds
Introduction to Smooth Manifolds 4.46 avg rating — 145 ratings
18.
Naive Set Theory
Naive Set Theory 4.23 avg rating — 612 ratings
20.
Probability Theory: Independence, Interchangeability, Martingales
Probability Theory: Independence, Interchangeability, Martingales really liked it 4.00 avg rating — 1 rating