CMPUT 466/566: Machine Learning

Fall 2020

Instructor: Lili Mou

Course Format

The course will be delivered remotely. UofA members (for credit or auditing) enjoy a private Google Meet lecture room, QA sessions with the instructor and TAs, as well as other social events.

Lecture time:

12:30 PM -- 1:50 PM, Tuesday and Thursday, 1-Sep-2020 ~ 7-Dec-2020

Course Description

Machine learning teaches a machine to learn from previous experience and makes a prediction for (possibly new) data. This course covers standard materials of a “Machine Learning” course, such as linear regression, linear classification, as well as non-linear models. In the process, we will have a systematic discussion on training criteria, inference criteria, bias-variance tradeoff, etc. The goal of the course is to build a solid foundation of machine learning, so there would be intensive math derivations in lectures, assignments, and exams.

Syllabus and Open-Access Information

Please refer to this link.

Lecture Notes