Bridging the gap between neural networks and functions
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Re: Bridging the gap between neural networks and functions
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#5It discusses the standard backpropagation optimization method in differential form and the functional approximation of neural networks, but doesn't discuss transformers at all that I could tell. I think the code might be helpful to some in understanding implementation, but so much is now done in accelerators that it doesn't really capture real implementations.
Re: Bridging the gap between neural networks and functions
#6https://github.com/runvnc/mlp/blob/master/neuralnetwork.cpp
https://github.com/runvnc/nnpapers/blob/master/hinton86.pdf
This article is also a very good explanation.
Re: Bridging the gap between neural networks and functions
#7Hmm, might be just me, this feels like a refresher for people who already understand NN and transformers. This will probably escape most devs. I've had a bit better luck with the fastai course which is a series of YouTube videos, so it's a slower pace but explained quite well without requiring a lot of understanding.
Re: Bridging the gap between neural networks and functions
#8The font on the site made it really hard to read.