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

5 credit hours
This is a project-based class that introduces neural nets, fuzzy systems, deep learning, kernel methods, Bayesian learning, and evolutionary algorithms for optimization, prediction, and classification. Algorithms are learned through implementation exercises and a team project. Parallel readings on complex systems provide the biological, philosophical, and historical background of machine learning by tracing its roots in neurobiology, sociobiology, statistics, and physics.

Prerequisite Course(s): MATH 2320
Prerequisite or Co-requisite Course(s): MATH 2310
Terms Typically Offered: fall