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: Baptiste Busch
- Teacher: Ludovic Sebastien Pierre Coullery
- Teacher: Bernardo Fichera
- Teacher: Lukas Huber
- Teacher: Valentin Kindschi
- Teacher: Marjorie Marie Joséphine Lasson
- Teacher: Ilaria Lauzana
- Teacher: Vaios Papaspyros