Consider the neural network with two hidden layers shown in the following Figure to answer the next $8$ questions. The input layer consists of $3$ features x$=($X$1,$ x$2,$ x$3],$ each hidden layer has two nodes and the output layer gives the probabilities $=91,52,3,94]$ over four classes $1,2,3$ and $4.$ The weight parameter on each arc is labeled on the figure. There are three sets of weights: a$,$ w$,$ B$.$ Now consider back propagation to compute gradients. What is a CORRECT formula for computing

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