Machine Learning

• The most extensively covered topic in the module was Machine Learning.
• The second coursework was a Machine Learning Coursework.
• We covered: Linear Categorisers (Lecture 2)
• Categorisation (Lecture 3)
• Genetic Algorithms (Lecture 5)
• Self Organising Map (Lecture 8)
• MLPs (Lecture 11)
• SVMs (Lecture 18)
• Deep Belief Nets (Lecture 19)
• Large Data Sets (Lecture 20) could also be considered part of Machine Learning.
• You need to know about cross validation. (2 Fold Tests)
• You need to know about the No Free Lunch Theorem, and what that means.