= Maschinelles Lernen - Theorie und Anwendung =

=== General Information ===

Maschinelles Lernen - Theorie und Anwendung is a 9 LP (9 ECTS) credits module.

||'''Lecture'''||Tuesdays, 10 - 12||
||'''Room'''||MAR 0.015||
||'''Exercise session'''||Tuesdays, 12 - 14 ||
||'''Room'''||MAR 0.015||
||<(^|2>'''Trainers'''||Prof. Dr. Klaus-Robert Müller (Responsible)||
||Gregoire Montavon ||
||'''Contact''' || gregoire.montavon@tu-berlin.de ||
|| '''ISIS''' || https://isis.tu-berlin.de/course/view.php?id=4266 ||

=== Topics ===

 * Embedding
 * Stationary Subspace Analysis
 * Auto-encoders
 * Canonical Correlation Analysis
 * Kernel methods for structured data
 * Neural networks for structured data
 * Structured output learning
 * One-class SVMs
 * Bioinformatics