EX1: Consider a fully connected neural network in the Figure below: xz[1]=w[1]x+b[1]a[1]=(z[1])z[2]=w[2]a[1]+b[2]a[2]=(z[2])L(y,a[2]) a) Assuming the activation function is a Sigmoid function, write the analytical expressions for derivatives with respect to the weights W, biases b, and input x. b) Assuming the activation function is an Identity function, f(x)=x, what would be the derivatives with respect to all the weights W and biases b ? Comment on why this activation function is such a bad choice for neural network learning