18.657 | Fall 2015 | Graduate
Mathematics of Machine Learning
Course Description
Broadly speaking, Machine Learning refers to the automated identification of patterns in data. As such it has been a fertile ground for new statistical and algorithmic developments. The purpose of this course is to provide a mathematically rigorous introduction to these developments with emphasis on methods and their …

Broadly speaking, Machine Learning refers to the automated identification of patterns in data. As such it has been a fertile ground for new statistical and algorithmic developments. The purpose of this course is to provide a mathematically rigorous introduction to these developments with emphasis on methods and their analysis.

You can read more about Prof. Rigollet’s work and courses on his website.

Learning Resource Types
notes Lecture Notes
assignment_turned_in Problem Sets with Solutions
Four lines showing 4 (0,1) patterns.
Two points on the real line are shattered by half-lines. (Image by Prof. Philippe Rigollet.)