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Labs and Seminars

In the seminar, we will discuss solutions to theoretical assignments. These assignments will be made available in advance, and students are encouraged to work on them beforehand.

During the seminars, we will also assign and explain the practical homework tasks. Students will be required to implement solutions and submit their code for automatic evaluation. Additionally, some assignments will involve writing a report that includes responses to the given problems. These reports will be evaluated manually.

  • All homeworks must be submitted through the upload system.
  • All code must be implemented in Python.
  • Deadlines will be set for the submissions.

Lab/Seminar plan

Week Date Topic Teacher Materials Notes / Homeworks Deadline
1 25. 9. seminar cancelled
2 2. 10. Seminar: Predictor Evaluation VF/JP (with solutions) Assignment of HW 1 6.11.2025
3 9. 10. Seminar: Probably Approximately Correct Learning VF/JP (with solutions) (there was an error in solution of Assignment 2c; bug fixed 2026-01-13) HW 2 13.11.2025
4 16. 10. Seminar: VC dimension VF/JP (with solutions)
5 23. 10. Seminar: Neural Networks JD/JP (with solutions)
6 30. 10. seminar cancelled
7 6. 11. Lab: Neural Networks JD/JP HW 3 11.12.2025
8 13. 11. Seminar: Support Vector Machines VF/JP (with solutions) HW 4 18.12.2025
9 20. 11. Seminar: Ensembling JD/JP (with solutions)
10 27. 11. Seminar: Gradient Boosting Machine JD/JP HW 5 We will only discuss the GBM assignment from last week and assign the new HW. Jakub
11 4. 12. Seminar: Generative learning, Maximum Likelihood estimator VF/JP (with solutions) HW6 1.1.2026
12 11. 12. Seminar: EM algoritm; Bayesian learning VF/JP HW7 8.1.2026
13 18. 12. seminar cancelled 🎁
14 8. 1. Seminar: (Hidden) Markov Models JD/JP (with solutions)
courses/be4m33ssu/labs.txt · Last modified: 2026/01/13 10:38 by xfrancv