EE 460 Machine Learning for Engineers

Units: 4
Overview of machine learning, regression and classification, clustering and dimensionality reduction, loss-functions, over/under-fitting, cross-validation, kernel machines, decision trees and neural networks.
Prerequisite: EE 155 or BME 210 or CE 108 or CHE 305 or CSCI 103 or ISE 150 or ITP 115 or ITP 165 or ITP 168
Recommended Preparation: Linear systems on the level of EE 301, probability and/or statistics on the level of EE 364 or MATH 407 or CE 119 or ISE 220 or ISE 225
Duplicates Credit in CSCI 467
Instruction Mode: Lecture, Discussion
Grading Option: Letter