MAT8034: Machine Learning

Southern University of Science and Technology, Spring 2026

Teaching Staff

	name	email	office hour
Instructor	Fang Kong	kongf@sustech.edu.cn	Mon 2-4 PM Room 315, Business School Building

News

Course Information

Lecture times: Mon 7:00-9:50 PM at Zhihua Building 108

Grading: Final exam (40%), project (40%), and assignments (20%)

References:

• CS229 Machine Learning by Stanford [Lecture notes link]
• Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto
• Pattern Recognition and Machine Learning by Christopher M. Bishop
• Elements of Statistical Learning by Travor Hastie, Robert Tibshirani, Jerome Friedman

Schedule

week	date	topic	materials
1	Feb 28	1 Introduction	pdf
		2 Linear Regression	pdf
2	Mar 2	3 Classification	pdf
		4 Generalized Linear Models	pdf
3	Mar 9	5 Generative Learning Algorithms	pdf
4	Mar 16	6 Deep Learning	pdf
5	Mar 23	7 Generalization and Regularization	pdf
		8 Clustering and K-means	pdf
6	Mar 30	9 EM Algorithms	pdf
		10 Markov Decision Processes (MDPs)	pdf
7	Apr 6
8	Apr 13	11 Markov Decision Processes (MDPs) 2	pdf
9	Apr 20	12 Reinforcement Learning	pdf
10	Apr 27	13 Exploration and Exploitation	pdf
		14 Function Approximation and Policy Methods	pdf
12	May 11	15 Deep RL	pdf
13	May 18	16 RL in LLMs	pdf
		Final Review	pdf