Statistical Learning
Summer 2022: Statistical Learning
Contents
The course introduces several important machine learning methods from a statistics perspective as well as basic concepts such as training and test data, resampling methods, overfitting and bias-variance tradeoff. Relevant theoretical background of the methods is provided, as well as illustrations for their application and interpretation in R.
General Information
Lecturer: Dr. Annette Möller
Type: Lecture (without exercises)
Recommended prerequisites: Sufficient background in statistics, basic knowledge of regression modelling and R
Module allocation: see eKVV
Location and Date: H3, Tuesdays 16-18 Uhr
Most lectures are planned offline in the Lecture Hall. A few lectures take place online via Zoom. Please check the announcements in the respective Lernraum regularly!