Q6 So Many Derivatives! 10 Points Consider the neural network configuration below: Wo XO Z W1 + 8(z) > y X1 X Q6.1 2 Points Which of the following decision boundaries can be learned by the neural network? Assume wo, w1, x0, x1, Ta E R" and z = word + w1x1. Let g(z) be the binary step activation function with Ta as the decision threshold, which is defined as follows: g (z) = 1 if z z Ta Oif z