This course Machine Learning provides a wide viewpoint on Machine Learning, covering classification, clustering, regression and feature reduction. The focus is on the general concepts of learning from data, generalisation and overtraining.

Aspects that will be covered are: multivariate statistics, dimension reduction, clustering, density estimation, classification and regression. More advanced topics in classification concerning representation, measurement types, regularisation, and classifier combination follow. Specific problems that will be highlighted are limited sample size, generalisation, bias/variance dilemma, the curse of dimensionality and model selection.

YearStartsEnds
2019-2020Jan 1, 2020