EENG 5433 - Machine Learning and Adaptive Control (3 Credit Hours)

Lecture Hours: 1-2 Lab Hours: 0
Machine Learning is one of the most widely applied technical fields in the academia and industry. The class covers fundamental algorithms in machine learning including linear regression, classification, neural networks, support vector machines, clustering, and introduction to reinforcement learning. This course also covers adaptive control algorithms: including direct and indirect adaptive control. Electrical Engineering applications are demonstrated in image processing, autonomous driving, and robotics.

Prerequisite(s): A minimum grade of “C” in EENG 3421 and prior or concurrent enrollment in EENG 5431.
Cross Listing(s): EENG 5433G.