Run gradient descent to minimize the functiong(w) = 1 50 w 4 + w 2 + 10w with an initial point w 0 = 2 and 1000 iterations. Make three separate runs using each of the steplength values = 1, = 10-1 , and = 10-2 . Compute the derivative of this function by hand, and implement it (as well as the function itself) in Python using NumPy. Plot the resulting cost function history plot of each run in a single figure to compare their performance. Which steplength value works best for this particular function and initial point