Please note:

To view the current Academic Calendar, go to

Mathematical and Probabilistic Foundations of Machine Learning CMPT 727 (3)

Using machine learning algorithms effectively requires understanding their theoretical and conceptual basis. Covers mathematical and probabilistic foundations of machine learning, placing learning methods in a unified framework based on Bayesian reasoning. Students will acquire skills for formulating models, deriving optimization algorithms, and choosing effective approaches for a given learning problem. Topics include parameter estimation, optimization, linear classification and regression, regularization, and probabilistic graphical models.

Section Instructor Day/Time Location
G100 Maxwell Libbrecht
We 1:30 PM – 2:20 PM
Fr 12:30 PM – 2:20 PM
WMC 2200, Burnaby
WMC 2200, Burnaby