Machine Learning, Neural Networks, Backpropagation, Gradient Descent.
sum of the effect of change in node 4 and node 5. We can calculate the effects in a similar way we calculated dE/dY5 So, we can generalize it to: where the ith node is in the Lth layer and the jth node is at the (L+1)th layer. Now, once we find, the change in error with a change in weight for all