GP-OML Course – Machine Learning
12 September 2024 09:30 till 15:00 | Add to my calendar
Fully booked
| Date | 12, 19 & 26 September & 10 October 2024 |
|---|---|
| Time | 09.30 – 12.00 h & 13.00 – 15.00 h |
| Location | Online |
| Lecturer | Prof. dr. Inneke Van Nieuwenhuyse (Hasselt University) and Prof. dr. David Wozabal (VU Amsterdam) |
| Days | 4 |
| ECTS | 1 (attendance only) | 4 (attendance + passing assignment) |
| Course fee | Free for TRAIL/Beta/ERIM members, others please contact the TRAIL office |
This course provides a comprehensive introduction to the fundamental principles of machine learning and statistical pattern recognition. It covers both the theoretical foundations and practical implementation of machine learning methods, guiding participants through the end-to-end process of data investigation using machine learning techniques. The objective is to either uncover new insights in areas with limited prior knowledge or achieve accurate predictions of future observations.
Beginning with an overview and characterization of machine learning methods, the course delves into general principles for data manipulation, feature engineering, model selection, calibration, and evaluation. It then focuses on supervised learning, specifically tree-based regression and classification models, which are currently considered state-of-the-art for tabular data as well as on Gaussian processes.
The morning sessions primarily emphasize theoretical aspects, while the afternoon sessions offer hands-on demonstrations of machine learning methods using Python. The course does not center around specific applications, as those are addressed in the optional project. Participants are encouraged to apply the foundational knowledge gained in the course to a machine learning application relevant to their own scientific domain. Throughout the sessions, examples of machine learning applications are provided for reference