Practical Course - Applied Machine Learning (IN2106, IN4192)
Course 0000000592 in SS 2024
General Data
Course Type | practical training |
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Semester Weekly Hours | 6 SWS |
Organisational Unit | Informatics 26 - Associate Professorship of Data Analytics and Machine Learning (Prof. Günnemann) |
Lecturers |
Dominik Fuchsgruber Stephan Günnemann Aman Saxena Leo Schwinn |
Dates |
Mon, 16:00–18:00, MI 02.07.014 and 1 singular or moved dates |
Assignment to Modules
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IN2106: Master-Praktikum / Advanced Practical Course
This module is included in the following catalogs:- Further Modules from Other Disciplines
Further Information
Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.
additional remarks | Development of reliable machine learning methods (e.g. robustness and uncertainty), with major focus on learning principles for graphs (e.g. graph neural networks) and temporal data (e.g. point processes). |
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Links |
Course documents E-Learning course (e. g. Moodle) TUMonline entry |