MATH 590STA: Introduction to Mathematical Machine Learning (2024 Spring)

Course Description:

This course will provide an introduction to machine learning from a mathematical perspec- tive. The primary objective of this course is to cultivate in students a sense of mathemat- ical curiosity and equip them with the skills to ask mathematical questions when studying machine learning algorithms. Classical supervised learning methods will be presented and studied using the tools from information theory, statistical learning theory, optimization, and basic functional analysis. The course will cover three categories of machine learning ap- proaches: linear methods, kernel-based methods, and deep learning methods, each applied to regression, classification, and dimension reduction. Coding exercises will be an essential part of the course to empirically study strengths and weaknesses of methods.