I’ve become increasingly interested in fully understanding what Zeiler and Fergus did in visualizing the hidden layers in a neural network. There’s some good information in this post from last year. In particular I’m interested to see if it’s possible to do this for NLP as well as image recognition (but just implementing it with current fastai tools for imagery would be a great start).
To me it seems critically important to understand the progression that the network is going through, at least inasmuch as as human beings can recognize and understand it, in order to arrive at an answer.
If anyone is interested in collaborating or contributing, please let me know!
Thanks,
David