Consider a feedforward neural network that performs regression on a p -dimensional input to produce a scalar output. It has m hidden layers and each of these layers has k hidden units. What is the total number of trainable parameters in the network? Ignore the bias terms. pk+mk2 pk+mk2+k pk+(m−1)k2+k p2+(m−1)pk+k p2+(m−1)pk+k2
