ECEGR 4750 - Machine Learning I: Optimization, Prediction, and Pattern Recognition in Complex Systems

5 credit hours
This class is a project-based introduction to machine learning. Topics are drawn from neural networks, deep learning, Bayesian learning, evolutionary algorithms, and instance-based learning. Coding exercises, demos, and a team project provide hands-on and active learning. Problems of AI ethics are addressed through reading and discussion. Further (optional) readings connect machine learning to its roots in psychology, physics, neurobiology, sociobiology, and statistics.

Prerequisite Course(s): MATH 2320
Prerequisite or Co-requisite Course(s): MATH 2310