Labs
| Datum | Č.T. | S/L | Náplň | Učitel | Materiály | Úkol |
|---|---|---|---|---|---|---|
| 23-25.09.2024 | 1 | L | Intro: Introduction to the course and machine learning. | AK | ||
| 30.9-02.10.2024 | 2 | S | 1D regression and 2D classification: Revision of the regression and classification theory, analytic gradient computation, gradient in computational graph and loss minimization. | KZ | template_for_students.zip labs_02_regression.pdf | |
| 07-09.10.2024 | 3 | L | Loss, MLP | AK | HW01 - MLP | |
| 14-16.10.2024 | 4 | S | Autograd: Computational graphs, backpropagation and the automatic gradient computation. | JV | lab04.zip lab04.pdf lab04_ref.zip | |
| 21-23.10.2024 | 5 | L | CNN: Introduction to the convolution and convolution neural network. | JV | lab05.zip lab05_ref.zip | HW02 - Autograd |
| 28-30.10.2024 | 6 | S | Independence day | Preparation for midterm test | ||
| 04-06.11.2024 | 7 | L | HPC: High performace computing tutorial. | RS | lab06.zip lab06_ref.zip | |
| 11-13.11.2024 | 8 | S | Optimization: Convergence rate, oscillations, diminishing gradients. | KZ | optimizers_student_template.py.zip    | |
| 18-20.11.2024 | 9 | L | Layers: | RS | hw03.zip | HW03 - segmentation |
| 25-27.11.2024 | 10 | S | Transformers I: Introduction to the transformer architecture, GPT2 | DC | lab10.zip lab10_ref.zip | |
| 02-04.12.2024 | 11 | L | Transformers II: Intro into ViTs | DC | HW04 - Transformers | |
| 09-11.12.2024 | 12 | S | RL I Intro: Introduction to the reinforcement learning. Policy gradient. | DK | rl_lab_1.pdf | |
| 16-18.12.2024 | 13 | L | RL II - Deep learning: Deep reinforcement learning. | DK | HW05 - RL | |
| 06-08.01.2024 | 14 | S |