Prerequisites: CS 100, STAT 155
Description: CS 229 online section; enrollment in the Online Master-in-Science in Engineering program A study of supervised machine learning that emphasizes discriminative methods. Covers the areas of regression and classification. Topics include linear methods, instance-based learning, neural networks, kernel machines, and additive models.
Credit: May be taken Satisfactory (S) or No Credit (NC) with consent of instructor and graduate advisor.