skip to main content

Course Websites

CS 598 PSO - Mach Lrng for Signal Processng

Spring 2021

Official Description

Subject offerings of new and developing areas of knowledge in computer science intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: May be repeated in the same or separate terms if topics vary.

Section Description

For up-to-date information about statistics course registration, please see our registration update pages:

Related Faculty

Course Description

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. The course will consist of lectures and student projects and presentations. Students are expected to have a working knowledge of linear algebra, probability theory, and programming skills to carry an implementation of a final project (preferably in MATLAB, but all languages are welcome).

Credit Hours

4 hours


Undergraduate degree and courses in linear algebra and probability theory.

Practical Statistical LearningPSO40235E104 -    Feng Liang