https://cw.fel.cvut.cz/b251/ 2026-04-19T08:52:58+0200 https://cw.fel.cvut.cz/b251/ https://cw.fel.cvut.cz/b251/lib/tpl/bulma-cw/images/favicon.ico text/html 2025-09-21T12:17:27+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b251/courses/becm33dpl/tutorials/hw1?rev=1758449847&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 2025-09-21T12:09:40+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b251/courses/becm33dpl/tutorials/hw2?rev=1758449380&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 2025-11-07T15:55:36+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b251/courses/becm33dpl/tutorials/hw3?rev=1762527336&do=diff HW 3 - CNNs All information regarding the third homework assignment can be found here: UROB HW3 – Fruit Image Analysis Repository ---------- 🍎 Overview This homework focuses on training a Convolutional Neural Network (CNN) to: ClassifySegmentLearn The goal is to design, train, and evaluate a model capable of performing all three tasks efficiently. text/html 2025-12-03T12:43:38+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b251/courses/becm33dpl/tutorials/hw4?rev=1764762218&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 2025-09-21T12:13:43+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b251/courses/becm33dpl/tutorials/hw5?rev=1758449623&do=diff HW 5 - 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 2025-11-26T12:14:45+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b251/courses/becm33dpl/tutorials/start?rev=1764155685&do=diff Labs The labs have the same structure as B3B33UROB course UROB Course github UROB Course pages Lab schedule Date Week Topic Resources Homework assignment 24.9.2025 1 Intro: Introduction to the course and machine learning. Classification 1.10.2025 2 1D regression and 2D classification: Revision of the regression and classification theory, analytic gradient computation, gradient in computational graph and loss minimization.