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Machine Learning and Physics (MKTP6)
Wintersemester 2025/2026
Dozent: Bereau T, Hamprecht F
187 Teilnehmer/innen
Dozent: Bereau T, Hamprecht F
187 Teilnehmer/innen
Course website
https://sciai-lab.org/teaching/25w/mlph/
Recommended textbooks
- Murphy, Probabilistic Machine Learning: An Introduction, https://probml.github.io/pml-book/book1.html
- Hastie, Tibshirani, Friedman, The Elements of Statistical Learning, https://link.springer.com/book/10.1007/978-0-387-84858-7
- Prince, Understanding Deep Learning, https://udlbook.github.io/udlbook/
- Bishop, Bishop, Deep Learning, https://link.springer.com/book/10.1007/978-3-031-45468-4
Requirements for admission to the exam
Threshold of 50% average points on the weekly exercises
Weekly exercises
- Due every Monday, 13:59
- Submit in pairs (i.e., groups of two)
- Upload on PhÜ one document per group of two
Curriculum (tentative)
Materialien
Übungsgruppen
- Gruppe 1 (Lorenz Vogel)
28 Teilnehmer/innen
Phil 12 kHS, Mo 16:15 - 18:00 - Gruppe 2 (Christof Gehrig)
28 Teilnehmer/innen
INF 227 03.404, Di 14:15 - 16:00 - Gruppe 3 (Sander Hummerich)
27 Teilnehmer/innen
Phil 12 kHS, Di 16:15 - 18:00 - Gruppe 4 (Antoine Petitjean)
28 Teilnehmer/innen
INF 227 01.403, Mi 16:15 - 18:00 - Gruppe 5 (Gerrit Gerhartz)
24 Teilnehmer/innen
Phil 12 kHS, Do 14:15 - 16:00 - Gruppe 6 (Roman Remme, Peter Lippmann)
28 Teilnehmer/innen
INF 227 03.402, Fr 14:15 - 16:00
