CS545 - Machine Learning for Signal Processing

Course Information

Course Subject

Today we see an increasing need for machines that can understand complex real-world signals, such as speech, images, movies, music, biological and mechanical readings, etc. In this course we will cover the fundamentals of machine learning and signal processing as they pertain to this goal, as well as exciting recent developments.

We will learn how to decompose, analyze, classify, detect and consolidate signals, and examine various commonplace operations such as finding faces from camera feeds, organizing personal music collections, designing speech dialog systems and understanding movie content.

Grading will be based on 4-5 homework assignments and a final project.

Attending the course

The course will be in-person at Siebel 1404, Tuesdays and Thursdays 12:30-13:45. Lectures will be recorded and shared after the class, but students are encouraged to come to the lectures and participate in discussions.

The lecture room has 4-5x the capacity of the class size and social distancing should be easy to maintain.

Campuswire: We will be using campuswire for asynchronous Q&A and to distribute class material. Please add youself to the class using the link below (code 5471):


Course staff

Paris Smaragdis <paris@illinois.edu> (Instructor)

Zhepei Wang <zhepeiw2@illinois.edu> (TA)

Class calendar

All lectures and TA hours will be added in this calendar

Note: You can only see this calendar if you are logged in with your google@illinois account