b) Given the following neural network with initialized weights as in the picture, explain the network architecture knowing that we are trying to distinguish between dogs and cats and an example of training tupples is as follows: T1{0.6, 0.1, dog}, T2{0.2, 0.3, cat}. 10 -0.1 7 0.6 output neurons -0.4 -0.2 0.2 0.1 0.6 -0.1 hidden neurons 3)0.1 4 0.2 5 0.5 -0.2 0.2 0.1 0.3/-0.4 1 input 2 neurons he Let the learning rate be 0.1 and the weights be as indicated in the figure above. Do forward propagation of the signals in the network using Tl as input, then perform the back propagation of the error. Show the changes of the weights. Hint: Encoding of the outputs may be 10 for class "dog", 01 for class "cat" b) Given the following neural network with initialized weights as in the picture, explain the network architecture knowing that we are trying to distinguish between dogs and cats and an example of training tupples is as follows: T1{0.6, 0.1, dog}, T2{0.2, 0.3, cat}. 10 -0.1 7 0.6 output neurons -0.4 -0.2 0.2 0.1 0.6 -0.1 hidden neurons 3)0.1 4 0.2 5 0.5 -0.2 0.2 0.1 0.3/-0.4 1 input 2 neurons he Let the learning rate be 0.1 and the weights be as indicated in the figure above. Do forward propagation of the signals in the network using Tl as input, then perform the back propagation of the error. Show the changes of the weights. Hint: Encoding of the outputs may be 10 for class "dog", 01 for class "cat