https://cw.fel.cvut.cz/b241/ 2026-04-27T13:38:33+0200 https://cw.fel.cvut.cz/b241/ https://cw.fel.cvut.cz/b241/lib/tpl/bulma-cw/images/favicon.ico text/html 2024-09-23T14:29:01+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b241/courses/b3b33urob/tutorials/hw1?rev=1727094541&do=diff HW 1 - Classification In this homework, you'll begin by revisiting the fundamentals of classification. Subsequently, you'll implement a straightforward classifier. Following that, you will delve into more advanced classifiers utilizing deep learning techniques. Upon completing this assignment, you will have a comprehensive grasp of classification. text/html 2024-10-21T10:09:05+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b241/courses/b3b33urob/tutorials/hw2?rev=1729498145&do=diff HW 2 - Autograd In this assignment, it would be your task to implement your own autograd library, similar to the one shown in the lab. The difference is that while in the lab, we showed autograd for scalar values, your solution shall also work with vectors and tensors. text/html 2024-12-13T19:41:02+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b241/courses/b3b33urob/tutorials/hw3?rev=1734115262&do=diff HW 3 - Segmentation In this assignment, your task will be to train a neural network with multi-loss objective, namely: hierarchical classification and semantic segmentation. The dataset consists of images of pets, where each image corresponds to a species ( text/html 2024-12-12T11:50:43+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b241/courses/b3b33urob/tutorials/hw4?rev=1734000643&do=diff HW 4 - Vision Transformer In this assignment, you will implement a Vision Transformer (ViT) from scratch for satellite image classification using the EuroSAT dataset. You'll build and understand the core components of transformer architecture applied to computer vision tasks. text/html 2024-12-17T23:29:53+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b241/courses/b3b33urob/tutorials/hw5?rev=1734474593&do=diff HW5 - Deep Reinforcement Learning This homework serves as an introduction to deep reinforcement learning methods. Your goal will be to implement a particular approach to RL known as policy gradient, where a neural network learns to control a given dynamic system through interaction. text/html 2022-09-26T14:03:18+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b241/courses/b3b33urob/tutorials/lab_01?rev=1664193798&do=diff Intro to Numpy and Pytorch Python You will be using python in this subject, as well as in many of your subjects throughout the Bachelors and Masters course. Python is extremely flexible and powerful, mostly due to the ease of use and the vast amount of available libraries for almost anything. We will be using python 3 (do not use python 2). Any version above 3.6 should be fine. Q: Isn't python slow? Yes, python is an interpreted language so it is slow. When performing computation / optimi… text/html 2024-12-20T19:39:12+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b241/courses/b3b33urob/tutorials/start?rev=1734719952&do=diff 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.