. Suppose we are interested in predicting a numeric rating for movie reviews. Specifically, our predictor takes a movie review x and returns σ(w (x)), where (x) is the features of x, w is the weight parameters, and σ(z) = (1+e¯²)−¹ is the sigmoid function that squashes a real number z to range (0,1). Assume that the movie rating y is a real number in range (0, 1). Assume that we are using the squared loss. (a) Write out the expression for Loss(x, y, w) for a single example (x, y). (b) Compute the gradient of the loss with respect to w. Hint: do (2) == dz = σ(z)(1 − σ(z))