Master Lab Course - Explainable AI for Machine Learning (IN2106, IN4286)
Lehrveranstaltung 0000003487 im WS 2020/1
Basisdaten
| LV-Art | Praktikum |
|---|---|
| Umfang | 5 SWS |
| betreuende Organisation | Informatik 2 - Lehrstuhl für Sprachen und Beschreibungsstrukturen in der Informatik (Prof. Seidl) |
| Dozent(inn)en |
Edoardo Mosca Leitung/Koordination: Georg Groh |
| Termine |
Zuordnung zu Modulen
-
IN2106: Master-Praktikum / Advanced Practical Course
Dieses Modul ist in den folgenden Katalogen enthalten:- weitere Module aus anderen Fachrichtungen
weitere Informationen
Lehrveranstaltungen sind neben Prüfungen Bausteine von Modulen. Beachten Sie daher, dass Sie Informationen zu den Lehrinhalten und insbesondere zu Prüfungs- und Studienleistungen in der Regel nur auf Modulebene erhalten können (siehe Abschnitt "Zuordnung zu Modulen" oben).
| ergänzende Hinweise | A considerable amount of research and applications leverages machine learning techniques to solve several real-life tasks. While learning directly from the data is a major key for their success in terms of automation and performance, methods are progressively becoming more complex and opaque to humans. Most famously, Deep Neural Networks have gained popularity due to their success in practice but behave like black-boxes. In this course, we explore solutions coming from the recent research field of eXplainable Artificial Intelligence (XAI). In particular, we focus on the practical development of interpretable models and the application of explainability techniques to understand black-box frameworks. Therefore, we provide a range of related research literature based on which students develop concrete projects towards making machine learning techniques and predictions understandable for humans. We potentially encourage the participants to use cutting-edge machine learning models such as neural networks and engage themselves in several fields of applications such as Natural Language Processing, Computer Vision, and Machine Learning on Graphs. |
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| Links |
Zusatzinformationen TUMonline-Eintrag |
Gleiche Lehrveranstaltungen (z. B. in anderen Semestern)
| Semester | Titel | Dozent(en) | Termine |
|---|---|---|---|
| WS 2022/3 | Master Lab Course - Explainable AI for Machine Learning (IN2106, IN4286) |
Eder, T.
Mosca, E.
Leitung/Koordination: Groh, G. |
Mi, 10:00–12:00, MI 01.07.014 sowie einzelne oder verschobene Termine |
| WS 2021/2 | Master Lab Course - Explainable AI for Machine Learning (IN2106, IN4286) |
Eder, T.
Mosca, E.
Leitung/Koordination: Groh, G. |
Mo, 09:00–11:00, MI 01.09.014 Mo, 10:00–12:00, MI 02.07.014 |