The goal is to enable the students to understand the fundamental statistical machine learning algorithms for diverse datasets. To this end, the theory of these algorithms is developed in the lectures and during the practice sessions, many such data sets are analyzed.
Knowledge of the statistical machine learning approaches for diverse data sets and the ability to apply the appropriate algorithm for successfully solving a given machine learning problem.
The module is based on the excellent and freely available book: "An Introduction to Statistical Learning" by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani. This book has also a useful website http://www-bcf.usc.edu/~gareth/ISL/
(Durchführung gemäss Stundenplan)