Philosophy & Economics

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Hier können Sie die Daten dieser Veranstaltung
im Intranet der Fachgruppe Philosophie sehen.

Veranstaltungstitel Machine Learning in Neuroscience
Kennzeichen 50306 (BA) / 50311 (MA)
Veranstaltungsart Blockseminar
Fachgruppe Philosophie
Semester Sommer 2023
Dozent(en) Lena Kästner
Empfehlung(en) Studiensemester 4. Semester (P&E Bachelor)
6. Semester (P&E Bachelor)
BA höhere Fachsemester (> 6) (P&E Bachelor)
2. Semester (P&E Master)
4. Semester (P&E Master)
Bereich(e) P5*: Wissenschaftstheorie II
P6.v: Theoretische Philosophie
MA Electives




Machine Learning (ML) involves training computer algorithms to learn from data, without being explicitly programmed. It has a wide range of applications, from image and speech recognition to predicting outcomes and making recommendations. Increasingly, ML is also used in scientific inquiry. In this course, we focus on its use and role in neuroscience—both as a tool and as a scientific framework. Along the way we shall explore some core concepts in the philosophy of science such as explanation, discovery, and pursuit, discuss scientific models and their relationship to the world, and look into the richly intertwined history of ML and neuroscience.

While the course format is primarily discussion-based, willingness to engage with some more technical literature from philosophy, neuroscience and ML is presupposed. Previous knowledge in theoretical philosophy and/or computer science will be helpful.


Please join the MS Teams Team for this course with the following code: 5suwm25.

For the preparatory session, please join on zoom: https://uni-

Erfordernisse zum Punkteerwerb

Presentation + Essay

Zugehörige Termine
von - bis Ort  
Thu. 13.04.2023 - Sat. 15.04.2023 S 6, GW II