Kursöversikt

Instructor: Anders Forsgren

Welcome to the WASP course Mathematics for Machine learning.

The course will be given at KTH with two pair of lecture days, Monday-Tuesday February 13-14 and Thursday-Friday March 9-10. Participation is expected. Practical information, including schedule and suggestions on hotels, can be found here.

Fortunately or not, mathematics in machine learning is unavoidable. The good thing is that it does not require much of it. The goal of this course is to give you a refresher (and sometimes even a new information) on most of the basic mathematical tools you might encounter when working with ML. We are going to cover four pillars: linear algebra, calculus, probability and optimization. The February lectures will cover the first two and the March lectures cover the last two.

We follow (very roughly) Part I of the following book: 

M. P. Deisenroth, A. A. Faisal, and C. S. Ong.  "Mathematics for Machine Learning" (freely available at https://mml-book.github.io/)

In order to pass the course, successful completion of two sets of homeworks is required.

Video recordings from the lectures when the course given in spring 2022 are available, as a complement.