Spring 2021 Course Descriptions
COMP 136-01 Statistical Pattern Recognition
M. Hughes
MW 4:30-5:45p, Online
K+ Block
Statistical foundations and algorithms for machine learning with a focus on Bayesian modeling. Topics include: classification and regression problems, regularization, model selection, kernel methods, support vector machines, Gaussian processes, Graphical models.
Prerequisite: Prerequisites: MATH 13 or 42; MATH 46 or 70; EE 104 or MATH 162; COMP 40 or COMP 105 or a programming course using Matlab. COMP 135, or COMP 131 are recommended but not required. Or permission of instructor.