====== Labs ======

^ datum ^ č.t. ^ S/L ^ náplň ^ Učitel ^ Tutoriály ^ Materiály ^
| 20.09.2021 - 23.09.2021 | 1  | L | Python, Numpy, Pytorch intro - Home exercise!| | [[courses:b3b33vir:tutorials:pytorch:start|NumPy & PyTorch tutorial]] | | 
| 27.09.2021 - 29.09.2021 | 2  | S | Optimization Task - Blackbox Legged Robot | KZ |  \\ | [[courses:b3b33vir:tutorials:hw01_pybullet|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 | [[courses:b3b33vir:tutorials:classification|Classification - Materials]] |
| 18.10.2021 - 20.10.2021 | 5  | L | //Classification - Convolutional Neural networks, Training, Hyperparameters, GPU servers  //  | PV |  | [[courses:b3b33vir:tutorials:hw02_classification|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 | |[[courses:b3b33vir:tutorials:hw3_-_lidar_segmentation|HW3]] |  
| 08.11.2021 - 10.11.2021 | 8  | S | // Work on Homeworks // |  | | |
| 15.11.2021 - 17.11.2021 | 9  | L | // Object detection I // | VS |[[https://drive.google.com/file/d/1qP4fDU8FlEQHeisj_4WnicsRbY6z5g6Q/view?usp=sharing|Object detection - video ]] [[https://drive.google.com/file/d/1Ac11qHeEx1d_nGqESEsT3KV5qhZPB9ky/view?usp=sharing| pdf ]]| [[courses:b3b33vir:tutorials:hw04|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 | | [[courses:b3b33vir:tutorials:hw05|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 | |