Winter Term 2024 (1860)
CMPUT 367 - Intermediate Machine Learning
★ 3 (fi 6)(EITHER, 3-0-0)
This course in machine learning focuses on higher-dimensional data and a broader class of nonlinear function approximation approaches. Topics include: optimization approaches (constrained optimization, hessians, matrix solutions), kernel machines, neural networks, dimensionality reduction, latent variables, feature selection, more advanced methods for assessing generalization (cross-validation, bootstrapping), introduction to non-iid data and missing data. Credit cannot be obtained for both CMPUT 367 and CMPUT 466. Prerequisites: CMPUT 204 and 267; one of MATH 115, 118, 136, 146, or 156.
LECTURE B1 (19348)
2024-01-08 - 2024-04-12
TR 15:30 - 16:50 (CAB 235)
CMPUT 605 - Topics in Computing Science
★ 3 (fi 6)(EITHER, 3-0-0)
LECTURE B13 (19930)
2024-01-08 - 2024-04-12
01:00 - 01:00 (TBD)