CMPUT 466 - Machine Learning Essentials

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

Faculty of Science

Learning is essential for many real-world tasks, including recognition, diagnosis, forecasting and data-mining. This course provides a broad overview of topics in machine learning, from foundational methods for regression, classification and dimensionality reduction to more complex modeling with neural networks. It will also provide the formal foundations for understanding when learning is possible and practical. This single course is an alternative to the more in-depth two-course sequence on machine learning with CMPUT 267 and 467. Prerequisites: CMPUT 204 or 275; any 300-level Computing Science course; MATH 125 or 127; one of MATH 115, 118, 136, 146, or 156; and one of STAT 141, 151, 161, 181, 235, 265, SCI 151, or MATH 181. Credit cannot be obtained in CMPUT 466 if credit has already been obtained for CMPUT 467.

No syllabi

Fall Term 2024

Lectures

Section Capacity Class times Login to view Instructor(s) and Location
LECTURE A1
(49247)
131
2024-09-03 - 2024-12-09 (TR)
12:30 - 13:50

Labs

Section Capacity Class times Login to view Instructor(s) and Location
LAB D01
(49248)
131
2024-09-03 - 2024-12-09 (M)
17:00 - 19:50