#StackBounty: #neural-network #deep-learning #backpropagation #cost-function #math Chain function in backpropagation

Bounty: 100

I’m reading a Neural Networks Tutorial. In order to answer my question you might have to take a brief look at it.

I understand everything until something they declare as "chain function":

enter image description here

It’s located under 4.5 Backpropagation in depth.

I know that the chain rule says that the derivative of a composite function equals to the product of the inner function derivative and the outer function derivative, but still don’t understand how they got to this equation.

Update:

Please read the article and try to only use the terms and signs that are declared there. It’s confusing and tough enough anyway, so I really don’t need extra-knowledge now. Just use the same "language" as in the article and explain how they arrived to that equation.


Get this bounty!!!

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