The aim of the group will be to go over the fundamentals of important topics in Machine Learning, such as Kernel methods, Support Vector Machines, Random Forrest and more. The aim will be to meet every other week, in person, starting in the Spring term of the 2023-2024 academic year. The material to be covered in each meeting will typically be a chapter or half a chapter from a book (such as “Pattern Recognition and Machine Learning” by Bishop or “The Elements of Statistical Learning” by Hastie). In each meeting, a member of the group will present the material; however the meetings are not lectures – discussion and interaction amongst the group is encouraged.

Date Presenter Topic To Read Author(s)
18 January Hector McKimm Kernel Methods Pattern Recognition and Machine Learning, Sections 6.1 - 6.3 Bishop
1 February   Gaussian Processes Pattern Recognition and Machine Learning, Section 6.4 Bishop
8 February   Support Vector Machines Pattern Recognition and Machine Learning, Section 7.1 Bishop