Lectures
- Monday: 11:10—12:00 at Lecture Theatre 2 - Appleton Tower
- Wednesday: 11:10—12:00 at Lecture Theatre A - 40 George Square Lecture Theatres
- Friday: 11:10—12:00 at Screening Room G.04 - 50 George Square
Tutorials
- Tuesday: 13:10—14:00 at 5.04 - Teaching Studio - Appleton Tower
- Tuesday: 14:10—15:00 at 5.04 - Teaching Studio - Appleton Tower
- Tuesday: 15:10—16:00 at 5.04 - Teaching Studio - Appleton Tower
Assessment
- 20% coursework
- 80% exam
Extensions are permitted (4 days) and extra time adjustments (ETA) of 7 days are permitted and can be combined. See the school policy.
Reading
- [B] Christopher Bishop, Pattern Recognition and Machine Learning, 2006
- [DFO] Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong, Mathematics for Machine Learning, 2020
- [LWLS] Andreas Lindholm, Niklas Wahlström, Fredrik Linsten, and Thomas B. Schön, Machine Learning - A First Course for Engineers and Scientists, 2022
- [M] Kevin Murphy, Probabilistic Machine Learning: An Introduction, 2022
- [SB] Shai Shalev-Schwartz and Shai Ben-David, Understanding Machine Learning, 2014
Only the sections or chapters mentioned in the calendar are required reading for this course.
Past versions
The past coursework, practice exams, and tutorial sheets can be found in the webpages above. Past exams can be found on exam papers online.