CMPUT 267: Machine Learning I

Course description

This course introduces the fundamental statistical, mathematical, and computational concepts in analyzing data. The goal for this introductory course is to provide a solid foundation in the mathematics of machine learning, in preparation for more advanced machine learning concepts. The course focuses on univariate models, to simplify some of the mathematics and emphasize some of the underlying concepts in machine learning, including how should one think about data; how can data be summarized; how models can be estimated from data; what sound estimation principles look like; how generalization is achieved; and how to evaluate the performance of learned models.

Prerequisites and corequisites follow the University Calendar listing for CMPUT 267.

Teaching assistants

To be announced.

Schedule

Lectures meet Tuesdays and Thursdays. Topics will be posted before the term begins.