CS 480 - Machine Learning

4 credits
Includes an introduction of machine learning algorithms that have proven successful in practical applications including both supervised and unsupervised learning. Examples are used to explore the circumstances in which each of the various methods (e.g., regression, classification, clustering, neural networks) are appropriate. Prerequisite(s): CS 257 or CS 266, and STAT 243Z and MTH 261 and MTH 281.
Grade mode designated on a CRN basis each term. Students should consult current term schedule.