July 2019
Intermediate to advanced
512 pages
19h 39m
English
Content preview from Hands-On Deep Learning Algorithms with Python
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Gradients with respect to input to the hidden layer weight, U
Computing the gradients of the loss function with respect to 
is the same as 
, since here also we take the sequential derivative of 
. Similar to , to compute the derivative of any loss with respect to , we need to traverse all the way back to .
The final equation for computing the gradient ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.