Geometric deep learning course. This DL generalization allows transferring prior physical knowledge to NN architectures. Book at arxiv.org Full playlist (including tutorial and seminar records)

Information for reflection :) Here is a nice Rust library that provides concepts of eventuals (observable snapshot of the most up-to-date value). Just check it and spend a couple of minutes to think about it.

Be careful while using Github actions for Windows. By default Windows uses Powershell not bash, but you may prefer to explicitly choose bash as a shell. See Github action documentation You can find some details about using Powershell here

Here is an example of flake8 plugin that prevents you from using numpy random fn. A nice example of analyzing a source code in python.

Aaaah! Today I faced a strange error message from docker. => ERROR [internal] load metadata for docker.io/library/python:3.8-slim-buster 0.6s ------ > [internal] load metadata for docker.io/library/python:3.8-slim-buster: ------ failed to solve with frontend dockerfile.v0: failed to create LLB definition: rpc error: code = Unknown desc = error getting credentials - err: exec: "docker-credential-desktop.exe": executable file not found in $PATH, out: `` Thanks to Bertrand C for the solution. In ~/.docker/config.json change credsStore to credStore Source