Statistical Machine Learning


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.

Kurse in diesem Modul

Statistical Machine Learning:
  • Linear regression
  • Classification
  • Resampling Methods
  • Linear Model Selection and Regularization
  • Moving Beyond Linearity
  • Tree-Based Methods
  • Support Vector Machines
  • Unsupervised Learning

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  An Introduction to Statistical Learning (

Vorlesung mit 2 Lektionen pro Woche
Praktikum mit 2 Lektionen pro Woche

Diese Beschreibung ist rechtlich nicht verbindlich! Weitere Informationen finden Sie in der detaillierten Modulbeschreibung.