===== Labs and Seminars =====
Two types of labs (tutorials) will be proposed for the course (alternating):
  * practical labs in which we explain and discuss practical homework tasks. Students will implement selected methods discussed in the course and experiment with them.
  * theoretical labs in which students will discuss solutions of theoretical assignments (published a week before the class).

The solutions of the practical labs have to be submitted using the [[http://cw.felk.cvut.cz/upload/|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. 

===== Lab/Seminar plan =====

^Week ^Date ^Topic ^Lecturer ^Materials ^Deadline/Notes ^
|  1  | 23. 9. | — none — | | |
|  2  | 30. 9. | **Seminar** | BF | {{:courses:be4m33ssu:sem_intro_examples_you.pdf| }} |
|  3  | 7. 10. | **Seminar: lecture 1,2 ** | VF | {{ :courses:be4m33ssu:seminar_1_2021.pdf | }}|
|  4  | 14. 10. | **Seminar: lecture 2,3 ** | VF | {{ :courses:be4m33ssu:seminar_2_ws2021.pdf | }} |
|  5  | 21. 10. | **Seminar: lecture 3,4** | VF/DB | {{ :courses:be4m33ssu:seminar_3_ws2021.pdf | }}| |
|  6  | 28. 10. | —  National Holiday —  | |  | |
|  7  | 4. 11. | **Lab: SO Perceptron** | VF/DB | {{ :courses:be4m33ssu:lab_so_perceptron_ws2021.pdf | }}; DP tutorial {{ :courses:be4m33ssu:dynamic_programming.pdf | }} | 2. 12.  |
|  8  | 11. 11.  | **Seminar: Neural Networks** | JD/DB | {{ :courses:be4m33ssu:seminar_ann_ws2021.pdf | }} [[https://atmos.washington.edu/~dennis/MatrixCalculus.pdf|Matrix Differentiation]]|
|  9  | 18. 11.| **Lab: Neural Networks** | JD | {{ :courses:be4m33ssu:lab_backprop_ws2021.pdf | }} {{ :courses:be4m33ssu:bp_src.zip |Code}} | 16. 12. |   
|  10  | 25. 11.| **Seminar: lecture 8** | BF/DB | {{ :courses:be4m33ssu:sem-glearn-mle-ws21.pdf| }} |
|  11  | 2. 12. | **Lab: EM algorithm** | BF/DB | {{ :courses:be4m33ssu:shape_em_binary.pdf | task}} {{ :courses:be4m33ssu:em_data.tgz | data}}| 07. 01. |
|  12  | 9. 12. | **Seminar: lecture 9** | BF/DB | {{ :courses:be4m33ssu:sem-em-bayesian-ws21.pdf| }}  |
|  13  | 16. 12. | **Seminar: lecture 10** | BF/DB | {{ :courses:be4m33ssu:sem-hmm1-ws21.pdf| }} |Open learning room: Wed, 15.12., 17:00 KN:G-105  |
|  14  | 6. 1. | **Seminar: Ensembling** | JD/DB | {{ :courses:be4m33ssu:seminar_ensembling_ws2021.pdf | }} |  |