**Mathematics for Machine Learning**

**By Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong**

This book provides great coverage of all the basic mathematical concepts for machine learning.

It is divided into two parts

**Part I: Mathematical Foundations**

- Introduction and Motivation
- Linear Algebra
- Analytic Geometry
- Matrix Decompositions
- Vector Calculus
- Probability and Distribution
- Continuous Optimization

**Part II: Central Machine Learning Problems**

- When Models Meet Data
- Linear Regression
- Dimensionality Reduction with Principal Component Analysis
- Density Estimation with Gaussian Mixture Models
- Classification with Support Vector Machines