ECE 44901 - Machine Learning

The purpose of this course is to provide a broad introduction to theoretical foundations, fundamental methods, techniques and algorithms as well as the latest progresses in machine learning with an emphasis on real-world problem solving. It covers learning theory, supervised learning, unsupervised learning, reinforcement learning and best practices in machine learning. Students will learn how to apply machine learning techniques to research or industry applications through interdisciplinary case studies and applications in machine learning.

Preparation for Course
P: ECE 30200 (or equivalent) and programming skills in Matlab or Python. Departmental approval required.

Cr. 3.