I'd note that the Fleuret books gives the foundation for basic deep learning whereas the OP seems to give the necessary foundations for Transformers and related machinery. These later addition what is now "AI" are in total at least as complicated as the original deep learning concepts. Not that just learning basic neural networks but the two book don't appear to cover the same ground.
It's a nice treatment of the subject, but I wish he would post a conventionally-formatted .PDF that puts every page on a full sheet of standard printer paper.
I'm v curious how you're incorporating this into your workflow. Is it that when you want to implement something you can call out to these books as rigorous reference material for your agents? I'd never thought of doing such a thing and am curious how you're doing it and how it's worked.
Is there any one who have recommended books on the attention architecture specifically? I have been interested in that for a long time but never gotten around to actually studying it.
https://cdn.filepost.dev/file/filepost/uploads/15/1578f21219...
8Gb of whitepapers/books...
Is there any one who have recommended books on the attention architecture specifically? I have been interested in that for a long time but never gotten around to actually studying it.