MLMath

This repository is part of our MLT もくもく会 Math Reading Sessions. It’s based on “Mathematics For Machine Learning” by Marc Peter Deisenroth, A Aldo Faisal, and Cheng Soon Ong, to be published by Cambridge University Press. https://mml-book.github.io/

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