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 W
Now we will see how to calculate the gradients of loss with respect to hidden-to-hidden layer weights, 
, for all the gates and the candidate state.
Let's calculate gradients of loss with respect to 
.
Recall the equation of the input gate, which is given as follows:
Thus, by the chain rule, we can write the following:
Let's calculate each of the terms in the preceding equation.
We have already seen how to compute the ...
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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.