COMP4670/8600 Statistical Machine Learning

This is a broad but thorough intermediate level course of statistical machine learning, emphasising the mathematical, statistical, and computational aspects.

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Statistical Machine Learning plays a key role in science and technology. Some of the basic questions raised are:

This course provides a broad but thorough intermediate level study of the methods and practices of statistical machine learning, emphasising the mathematical, statistical, and computational aspects. Students will learn how to implement efficient machine learning algorithms on a computer based on principled mathematical foundations. Topics covered will include Bayesian inference and maximum likelihood modelling; regression, classification, density estimation, clustering, principal and independent component analysis; parametric, semi-parametric, and non-parametric models; basis functions, neural networks, kernel methods, and graphical models; deterministic and stochastic optimisation; overfitting, regularisation, and validation.

The course will use Python 3 and Jupyter notebook for all tutorials, and assignment/exam questions involving programming.

Course Schedule

Course Staff

alex Alexander Soen
chamin Chamin Hewa Koneputugodage shidi Shidi Li
tianyu Tianyu Wang josh Josh Nguyen minchao Minchao Wu
katya Ekaterina (Katya) Nikonova ruiqi Ruiqi Li haiqing Haiqing Zhu
belona Belona Sonna dillon Dillon Chen rong Rong Wang
Barclay Barclay Zhang evan Evan Markou zhiyuan Zhiyuan Wu


Required: Christopher M. Bishop: Pattern Recognition and Machine, Springer, 2006 (selected parts), available here

We also recommend:

Course sites


Online quiz expectations

Paired assignment expectations

Video assignment

The video assignment is an individual assignment.

Late policy

This policy applies to Assignment 1, Assignment 2, and the video assignment.

Enrolment questions

To enrol in this course you must have completed the pre-requisites as per the COMP4670 or COMP8600 course description.

The topics covered in this course have some overlap with a number of courses in the major for Statistical Data Analytics. Please have a look at the first few tutorial sheets for an indication of the kinds of mathematics and statistics that we will build upon.

If ISIS does not let you enroll but you believe you should be able to (e.g. have taken equivalent courses as the pre-qreq in the different university), then submit a permission code application here.