https://cw.fel.cvut.cz/b192/ 2026-05-04T23:19:29+0200 https://cw.fel.cvut.cz/b192/ https://cw.fel.cvut.cz/b192/lib/tpl/bulma-cw/images/favicon.ico text/html 2020-04-30T15:43:30+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b192/courses/bev033dle/lab4?rev=1588254210&do=diff Lab 4: Finetuning Deep Learning (SS2020) computer lab (10p) Introduction In this lab we start from a model already pretrained on the ImageNet classification dataset (1000 categories and 1.2 million images) and try to adjust it for solving a small-scale but otherwise challenging classification problem. text/html 2020-04-13T22:27:51+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b192/courses/bev033dle/labs?rev=1586809671&do=diff Lab/Seminar information Two types of labs (tutorials) will be proposed for the course (alternating): The solutions of the practical labs have to be submitted using the upload system Submission Regulations You may choose from the following submission variants: text/html 2020-06-02T22:02:41+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b192/courses/bev033dle/lectures?rev=1591128161&do=diff Syllabus Lecture/ Practice Date Topic Lecturer Materials Notes Feedback / discuss 1. 19.2 Recap: linear classifiers, linear regression, logistic regression, loss function, empirical risk minimisation, regularisation BF [ slides] thread 20.2 (no lab) - text/html 2020-06-01T09:54:36+0200 Anonymous (anonymous@undisclosed.example.com) https://cw.fel.cvut.cz/b192/courses/bev033dle/start?rev=1590998076&do=diff BEV033DLE – Deep Learning Links: Lectures, Labs and Seminars Labs and Seminars Lab4-finetuning Overview The course introduces deep neural networks and deep learning – a branch of machine learning and artificial intelligence. It aims at providing the relevant algorithmic and theoretical concepts needed for successfully designing and training NNs. At the same time it strives at providing technical and practical skills in this domain.