By hand calculation. This is an exercise to check if you understand the maths behind gradient descent. We have one independent variable (x) and one dependent variable (y). There are only two data points: x = [2.5, 5.6] y = [5.16, 11.14] We want to build a linear model: y = w1*x+wo. The initial guess is w1=3; wo=2.5. The loss function is mean squared loss. (a) what is the current loss function value? (b) what is the current dL/dw for W1 and Wu? (C) using a learning rate of 0.01, what is your next guess for w? What is the new loss function with the new w? Did it smaller or larger? (d) try different learning rates, what learning rate is too large