Title: I was involved in machine learning and AI a few years ago, mainly before the onset of the new diffusion models, large transformers (GPT*), Graph NNs and Neural ODE stuff.<p>I am comfortable with autograd&#x2F;computation graphs, PyTorch, &quot;classic&quot; neural nets and ones used for vision-type applications, as well as the basics of Transformer networks (I&#x27;ve trained a few smaller ones myself) and RNNs.<p>Do you know of any good resources to slowly get back into the loop?<p>So far I plan on reading through the original Diffusion&#x2F;GPT papers and start going from there but I&#x27;d love to see what you think are some good sources. I would especially love to see some Jupyter notebooks to fiddle with as I find I learn best when I get to play around with the code.<p>Thank you
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