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 9)
• Categorisation (Lecture 10)
• Genetic Algorithms (Lecture 3)
• Self Organising Map (Lecture 14)
• MLPs (Lecture 12)
• SVMs (Lecture 13)
• Deep Belief Nets (Lecture 15)
• Large Data Sets (Lecture 21) 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.