Reference books
This course is self sufficient, and does not strictly follow a single text book. We recommend the following books to use as reference for the course.
- Artificial Intelligence: a Modern Approach (Third Edition) by Stuart Russell & Peter Norvig (2016). A digital version is available from the College library.
- Covers a lot more than just Machine Learning
- Machine Learning by Tom Mitchell (1997).
- A classic textbook for Machine Learning, albeit dated. The website gives you a few new draft chapters.
- Pattern Classification (Second Edition) by Richard Duda, Peter Hart & David Stork (2000).
- A classic Machine Learning reference book.
- Statistical Pattern Recognition (Third Edition) by Andrew Webb & Keith Copsey (2011).
- An accessible book with a good coverage of topics.