Given the graphic above, use Python code to answer the following questions:

(1) What is the initial activation function value of Node 1?
(2) What is the initial activation value of Node 2?
(3) What is the initial activation value of Node 3?
(4) Using your previously calculated values, what is the updated weight for the link connecting node 1 with node 3?

(5) Using the data you've calculated, what is the updated weight for the link connecting Node 2 with Node 3?  

(6) For the updated weight from input 1 to node 2, by how much does the weight increase or decrease?  

In the accompanying graphic of a multi-layer neural network, input x1 = 1 and input x2 = 3. Use your program to answer the following questions. 1 3 0.5 0.1 0.8 0.2 1 2 0.2 0.7 3 This set of problems involves using the Feed-forward, back propagation algorithm. Write a basic Feedforward, multilayer neural network progam and use the values in the accompanying graphic (see preceding webpage) to initialize your neural network (see preceding webpage), and set the following inputs and learning parameters: input X 1 and input x2 = 3 with eta = 0.1, a desired output of 0.95 and the weights as indicated in the graphic. Note that since there are no biases, do not include them nor update them. =