datum | č.t. | S/L | náplň | Učitel | Tutoriály | Materiály |
20.09.2021 - 23.09.2021 | 1 | L | Python, Numpy, Pytorch intro - Home exercise! | | NumPy & PyTorch tutorial | |
27.09.2021 - 29.09.2021 | 2 | S | Optimization Task - Blackbox Legged Robot | KZ |
| HW1 |
4.10.2021 - 6.10.2021 | 3 | L | Maximum Likelihood Estimate and Regression, Backpropagation | KZ | | |
11.10.2021 - 13.10.2021 | 4 | S | Classification - Data, Training skeleton, Baseline Model | PV | Classification - Materials | |
18.10.2021 - 20.10.2021 | 5 | L | Classification - Convolutional Neural networks, Training, Hyperparameters, GPU servers | PV | | HW2 |
25.10.2021 - 27.10.2021 | 6 | S | Classification - Overfitting and Regularization, Pre-training and Fine-Tunning | PV | | |
01.11.2021 - 3.11.2021 | 7 | L | Semantic Segmentation - Encoder & Decoder Architecture, 3D Autonomous Driving Use Case | PV | | HW3 |
08.11.2021 - 10.11.2021 | 8 | S | Work on Homeworks | | | |
15.11.2021 - 17.11.2021 | 9 | L | Object detection I | VS | Object detection - video pdf | HW4 |
22.11.2021 - 24.11.2021 | 10 | S | Object detection II | VS | | |
29.11.2021 - 1.12.2021 | 11 | L | Generative Adversarial Network (David Coufal) | DC | | HW 5 |
06.12.2021 - 08.12.2021 | 12 | S | Generative Adversarial Network (David Coufal) | DC | | |
13.12.2021 - 15.12.2021 | 13 | L | Reinforcement Learning I | KZ | | |
3.1.2022 - 5.1.2022 | 14 | S | How can we improve VIR? (ideas for new labs/HW/examples/demos…) | KZ | | |