a Problem 1. (10 points) We consider the following Fully Connected NN to solve a 4-class Classifi- cation Problem: - We have 5 units in the Input Layer; We have 10 Neurons in the first Hidden Layer, and 20 Neurons on the second Hidden Layer; We are applying ReLU Activation Functions to Hidden Layers; - We are using the SoftMax Activation Function on the Output Layer. How many Parameters (weights and biases) does this NN have? - a Problem 1. (10 points) We consider the following Fully Connected NN to solve a 4-class Classifi- cation Problem: - We have 5 units in the Input Layer; We have 10 Neurons in the first Hidden Layer, and 20 Neurons on the second Hidden Layer; We are applying ReLU Activation Functions to Hidden Layers; - We are using the SoftMax Activation Function on the Output Layer. How many Parameters (weights and biases) does this NN have