COMP8600 Statistical Machine Learning
S16 units8000-level
This course provides a broad but thorough introduction to the methods and practice of statistical machine learning. Topics covered will include Bayesian inference and maximum likelihood; 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.
- 2024S1
- 2025S1
- 2026S1
- 2027S1
Prerequisites in 2025
The handbook's wording is ambiguous; this is a person's reading of it
One of
Why it's read this way: Read in parallel with COMP8880, which states the same structure with a ";": COMP6670 alone, or all three bracketed groups.
Incompatible with COMP4670, COMP8960: you can't count both.
The handbook's wording, and when it changed
To enrol in this course you must have completed COMP6670 or COMP3670 OR COMP6710 or COMP6730 or COMP7230 or COMP1110 or COMP1730 AND COMP8410 or COMP8910 or COMP3425 AND STAT6039 . Incompatible with COMP4670 and COMP8960 .
To enrol in this course you must have completed COMP6670 or COMP3670 OR ( COMP6710 or COMP6730 or COMP7230 or COMP1110 or COMP1730 ) and ( COMP8410 or COMP8910 or COMP3425 ) and ( STAT6039 or STAT7039 ) Incompatible with COMP4670 and COMP8960 .
To enrol in this course you must have completed COMP6670 or COMP3670 . Incompatible with COMP4670 .
What it leads to in 2025
These courses name COMP8600 in their 2025 prerequisites: