CMPUT 499 - Topics in Computing Science

3 units (fi 6)(VAR, VARIABLE)

This topics course is designed for a one on one individual study course between a student and an instructor. Prerequisites for each section may differ and are defined by the instructor in the course outline.

CMPUT 605 - Topics in Computing Science

3 units (fi 6)(EITHER, 3-0-0)

CMPUT 467 - Machine Learning II

3 units (fi 6)(EITHER, 3-0-0)

This is the second course of a two-course sequence on machine learning, with a focus on extending to nonlinear modeling with neural networks and higher-dimensional data. Topics include: optimization approaches (constrained optimization, hessians, matrix solutions), deep learning and neural networks, generative models, more advanced methods for assessing generalization (cross-validation, bootstrapping), introduction to non-iid data and missing data. Prerequisites: CMPUT 204 and CMPUT 267; any 300-level Computing Science course; and one of MATH 101, 115, 118, 136, 146, or 156. Credit cannot be obtained in both CMPUT 367 and 467.

CMPUT 567 - Machine Learning II

3 units (fi 6)(VAR, VARIABLE)

This course expands on machine learning fundamentals with a focus on extending to nonlinear modeling with neural networks and higher-dimensional data. Topics include: optimization approaches (constrained optimization, hessians, matrix solutions), deep learning and neural networks, generative models, more advanced methods for assessing generalization (cross-validation, bootstrapping), introduction to non-iid data and missing data. Credit cannot be obtained for both CMPUT 467 and 567 or CMPUT 367 and 567.