CS5487: Machine Learning: Principles and Practice
This course introduces fundamental machine learning principles with an emphasis on mathematical derivation, algorithm design, implementation, and evaluation. Topics include statistical and Bayesian learning, clustering, dimensionality reduction, regression, discriminative classifiers, and kernel methods, with selected connections to modern machine learning.
Course Information
- Institution
- City University of Hong Kong (Dongguan)
- Term
- Fall 2026 · 3 credits · 13 teaching weeks
- Schedule
- Lecture: Monday, 9:30 AM–11:20 AM
Tutorial: Monday, 11:30 AM–12:20 PM - Venue
- AC5-514
- Instructor
- Kangning Cui · Email · AC4-422
Assessment
- Assignments 20%
- Midterm Examination 20%
- Course Project 30%
- Final Examination 30%
Assignments include theoretical and programming work. The course project applies machine learning to a real-world problem.
Course Materials
- Syllabus
- Lecture notes: to be posted
- Past papers: to be posted
- Example code: to be posted