Real-world engineering applications must cope with a large dataset of
dynamic variables, which cannot be well approximated by classical or
deterministic models. This course gives an overview of methods from
Machine Learning for the analysis of non-linear, highly noisy and multi
dimensional data. Lectures are accompanied by exercises and practice sessions on computer.
- Professor: Aude Billard
- Professor: Athanasios Polydoros
- Teacher: Walid Amanhoud
- Teacher: Nuno Ricardo Ferreira Duarte
- Teacher: Farshad Khadivar
- Teacher: Manu Srinath Halvagal
