A presentation/notebook that expresses my view on things to make PyTorch efficient that targets researchers in AI and other domains.
It is Work In Progress [WIP], and I plan on expanding it.
Meanwhile, if you find the content useful, please, feel free to:
- Share it with your friends and collegues.
- Play with the notebook and use the code/text as you see fit.
- Create an issue if you see issues like typos or mistakes.
- Create an issue if there are topics you would like to learn more about.
- Star the repository to bump my GitHub credibility :)
And, of course, have fun doing High Performance Computing with PyTorch!
Note: I used notebook=7.3.2
with integrated RISE in case you want to access/modify the slideshow mode.