week 01-01 CH01-CH01 (HW0 – Lab0) Course Introduction and Preliminaries
week 02-02 CH02-CH02 (HW1 – Lab1) Probability Distribution
week 03-03 CH03-CH03 (HW2 – Lab2) Linear Models for Regression
week 04-04 CH04-CH04 (HW2 – Lab2) Linear Models for Classification
week 05-05 CH05-CH05 (HW3 – Lab3) Neural Networks I
week 06-06 CH05-CH05 (HW3 – Lab3) Neural Networks II
week 07-07 CH06-CH06 (HW4 – Lab4) Kernel Methods
week 08-08 CH07-CH07 (HW4 – Lab4) Sparse Kernel Machines
week 09-09 CH01-CH04 (HW5 – Lab5) Review
week 10-10 CH01-CH04 (HW5 – Lab5) Midterm-exam
week 11-11 CH01-CH04 (HW6 – Lab6) Exam Revisit and Review
week 12-12 CH08-CH08 (HW6 – Lab6) Graphical Models
week 13-13 CH09-CH09 (HW7 – Lab7) Mixture Models and EM
week 14-14 CH10-CH10 (HW7 – Lab7) Approximate Inference
week 15-15 CH11-CH11 (HW8 – Lab8) Sampling Methods
week 16-16 CH12-CH12 (HW8 – Lab8) Continuous Latent Variables
week 17-17 CH13-CH13 (HW9 – Lab9) Sequential Data
week 18-18 CH01-CH11 (HW9 – Lab9) Final Project Presentation
评估形式 占考试总成绩百分比 % 违纪处罚 备注 Notes
出勤 Attendance
课堂表现 Class Performance
小测验 Quiz 3
课程项目 Projects 20
平时作业 Assignments 7
期中考试 Mid-Term Test 20
期末考试 Final Exam 40
期末报告 Final Presentation 10
其它(可根据需要改写以上评估方式)Others (The above may be modified as necessary)
1. Pattern Recognition and Machine Learning, by C. Bishop, Springer (required)
2. Artificial Intelligence:Structures And Strategies For Complex Problem Solving, 6th Ed.,
by G. F. Luger, 机械工业出版社