Consider a 3-layer neural network as a binary classifier whose parameters are (2) given by: ww.b4 w21, 22,62), w), w, b2, and w3, b) (1) ,,(1) (3) 5 The parameters w represent the jh weight of neuron i at layer 1. Assume that the linear function is used as the activation function in the hidden layers of the network and the sigmoid function is used at the output layer. a) Give the dimensions of A(), A(2), and A(3), the activation matrices of each layer. b) Suppose we have 10 samples of the input, what are the dimensions of the input matrix X? 1 c) Write the equation that computes the network's output function hub(x) as a function of the input.