Question: As shown in Figure 1 , we consider a simple neural network for binary classification that has two hidden layers and one output layer. Each

As shown in Figure 1, we consider a simple neural network for
binary classification that has two hidden layers and one output layer. Each of the layers has
a single neuron. The input layer has the input variable x in R, where R refers to real space.
The two hidden layers has units a[1] in R and a[2] in R, respectively, and the output layer has
one unit a[3] in R. The parameters include \theta

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