From this video by Andrew Ng around 5:00
How are $\delta_3$ and $\delta_2$ derived? In fact, what does $\delta_3$ even mean? $\delta_4$ is got by comparing to y, no such comparison is possible for the output of a hidden layer, right?
5 of 5
Updated the video link.
How to derive errors in neural network with the backpropagation algorithm?
qed
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