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Winter term 2023/2024

19330101 (V) /19330102 (Ü): Machine Learning for Data Science (VL/Ü)
The course provides an overview of machine learning methods and algorithms for different learning tasks, namely supervised, unsupervised and reinforcement learning. In the first part of the course, for each task the main algorithms and techniques will be covered including experimentation and evaluation aspects. In the second part of the course, we will focus on specific learning challenges ...
InstructorProf. Dr. Grégoire Montavon
TimeOct 17, 2023 - Feb 13, 2024
Lecture: Tuesday (4-6  p.m., lecture room Takustr. 9)  and Thursday (12-2 p.m., lecture room Takustr. 9)  Practice Seminar : (4-6 p.m., lecture room Takustr. 9, seminar room 005) and  Friday (8-10 a.m., Takustr. 9, seminar room 005).
19333417: Explainable AI for Data Science (Seminar/Proseminar)
Explainable AI is a recent and growing subfield of machine learning (ML) that aims to bring transparency into ML models without sacrificing their predictive accuracy. This seminar will explore current research on the use of Explainable AI for extracting insights from large datasets of interest. Use cases in biomedicine, chemistry and earth sciences will be covered. Students will select a few ...
InstructorProf. Dr. Grégoire Montavon
TimeOct 20, 2023 - Feb 16, 2024
freitags, 14-16 Uhr
19334717: Machine Learning for Process Control (Seminar/Proseminar)
Numerous real-world processes need to be kept under control in order to ensure safety or efficiency. Machine learning models are good candidates for this. They can for example detect shifts/anomalies/decalibrations/instabilities/etc. and possibly also predict which action needs to be taken on the process. The real-time nature of such tasks brings unique challenges from a ML perspective compared ...
InstructorProf. Dr. Grégoire Montavon
TimeOct 20, 2023 - Feb 16, 2024
Friday 4-6 p.m.