Unsupervised Learning HT23

This course is taught in English

The aim of the course is to introduce basic and modern concepts of statistical learning without training labels - unsupervised statistical learning, with applications in statistical data analysis. Central concepts covered include similarity measures, linear and nonlinear methods of dimensional reduction, combinatorial, distributional and density-based methods of cluster analysis, hierarchical methods and different validation methods.

Class Schedule

Please note that self-enrollment on the course page is not the same as course registration in Ladok.