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b241
courses
b3b33urob
resources
Table of Contents
Resources
HW
SW
External educational materials
Resources
Brute specification
HW
Your own computer (best for debugging)
Servers with GPUs
Google Colab
Allows using GPU runtimes for 12 hours a day (also TPUs with Tensorflow)
Allows to link Google Drive with faculty account
SW
PyTorch
(install via pip / conda, load as a module on the servers)
PyCharm (educational licence at
download.cvut.cz
or
Official webpage
)
Setting a remote editor with PyCharm
Google Colab
Fast and easy simulation with Pybullet
External educational materials
Neural networks Stanford
YouTube lectures
Neural Networks - 3Blue1Brown
YouTube playlist
Deep Learning - Josh Starmer
YouTube playlist
Neural Networks Visualized - vcubingx
YouTube playlist
Understanding KL Divergence - Adian Liusie
YouTube video
Understanding Cross-Entropy - Adian Liusie
YouTube video
A Short Introduction to Entropy, Cross-Entropy and KL-Divergence - Aurélien Géron
YouTube video
Building an autograd library - Andrej Karpathy
YouTube video
courses/b3b33urob/resources/start.txt
· Last modified: 2024/10/16 11:42 by
vlkjan6