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Labs and Seminars

Two types of tutorial classes will be proposed for the course:

  • practical labs in which we explain and discuss practical homework tasks. Students will implement selected methods discussed in the course and experiment with them.
  • seminars in which we discuss solutions of theoretical assignments (published a week before the class). Students are expected to work on them in advance.

The solutions of the practical labs have to be submitted using the upload system

  • Your task will be to program a solution of the assigned problems. You have to hand out your code and a report in PDF. The report has to contain only answers to the assignments (nothing else).
  • As a programming language you can use either Matlab or Python.
  • The deadline for submitting your solutions will be 4 weeks after the date of assignment. This is a hard deadline.
  • Please notice that you have to submit your code and your report (PDF). The homework will be assessed with zero points if any of the two is missing.

Lab/Seminar plan

Week Date Topic Teacher Materials Deadline/Notes
1 22. 9. Seminar BF no assignments
2 29. 9. Seminar: lecture 1 VF/DB
3 6. 10. Seminar: lecture 2 VF/DB
4 13. 10. Seminar: lecture 2,3 VF/DB
5 20. 10. Seminar: lecture 3,4 VF/DB
6 27. 10. Lab: SO Perceptron VF/DB 25. 11. (extended by one day)
7 3. 11. Seminar: Neural Networks JD/DB Matrix Differentiation
8 10. 11. Lab: Neural Networks JD Code 8. 12.
9 17. 11. — National Holiday —
10 24. 11. Seminar: lecture 8 BF/DB
11 1. 12. Lab: EM algorithm BF/DB task data 05. 01.
12 8. 12. Seminar: lecture 9 BF/DB
13 15. 12. Seminar: lecture 10,11 BF/DB
14 12. 1. Seminar: Ensembling JD/DB
courses/be4m33ssu/labs.txt · Last modified: 2022/12/14 11:49 by drchajan