Advanced data analysis

What it covers

This unit introduces the problem of machine learning and the major kinds of statistical learning used in data analysis. Learning and the different kinds of learning will be covered and their usage discussed. Evaluation techniques and typical application contexts will presented. A series of different models and algorithms will be presented in an exploratory way: looking at typical data, the basic models and algorithms and their use: linear and logistic regression, support vector machines, Bayesian networks, decision trees, random forests, k-means and clustering, neural-networks, deep learning, and others. Finally, two specialist topics will be covered briefly, statistical learning theory and working with big data.

Assessment

When and where