Welcome to Mathematics of Machine Learning, taught by Adam Prügel-Bennett. The course covers the mathematical foundations that machine learning is built on — calculus, linear algebra, optimisation and probability — and how they are used in practice.
The course is dual coded: AICE3001 for third-year undergraduates and AICE6002 for MSc students. The lectures are shared; the assessment differs.
Problem sheets are worked through in the Friday tutorial session. Each one is linked from the timetable in the week it is used.