Department > Lectures > Winter Term 2025/2026 > Machine Learning and Physics (MKTP6)

Machine Learning and Physics (MKTP6)

winter term 2025/2026
Lecturer: Bereau T, Hamprecht F
188 participants

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)

See https://sciai-lab.org/teaching/25w/mlph/

Practice groups

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Machine Learning and Physics (MKTP6)
winter term 2025/2026
Bereau T, Hamprecht F
188 participants
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