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Backpropagation calculus | Deep Learning Chapter 4

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先只看一个权重:它改变加权输入,后者改变激活,激活再改变代价。链式法则把局部变化率相乘;向更早的层重复这个计算就得到反向传播。

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This right here is the chain rule, where multiplying together these three ratios gives us the sensitivity of c to small changes in WL.

Also, and this is where the idea of propagating backwards comes in, you can see how sensitive this cost function is to the activation of the previous layer.

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