Can someone help me with these questions?

y f(x1;w)- y1 = ewx1 - y1 E(w) = (ewx1 - y1)2 2.0 . (2, 2) 15 1.5 10 1.0 5 0.5 -1.5 1.0 0.5 0.5 1.0 15 W 0.1 0.2 0.3 0.4 0.5 0.6 0.7 W X (a) (b) (c) Figure 1: (a) A dataset of one data instance; (b) the corresponding f (x;; w) - yi; (c) the corresponding E(w) = (f(x;; w) - yi)2. Figure 1 (a) shows a dataset of just one data instance: (x1, y1 ) = (2,2). Now we want to fit a nonlinear curve f (x; w) = ewx to the dataset, using the sum of square error (SSE): E(w) = (f(x;;w) -y;)2. Figures 1 (b) and (c) show the curve f (x;; w) - yi w.r.t. w and the curve E(w) w.r.t. w, respectively.GaussNewton method Use the GaussNewton method to find the result that minimizes E (w) Note that, the optimal solution is 0.347. Since the GaussNewton method is an iterative method, the solution depends on the number of iterations. 1. Begin with the initialization 170(0) 2 1.5, perfonn three iterations of GaussNewton to get 179(3). What is 1713(3) (a numerical value)? 2. Begin with the initialization 1717\"\" = 0.0, perform three iterations of Gauss-Newton to get 1717(3). What is 1717(3) (a numerical value)? 3. Begin with the initialization 170(0) 2 1.0, perform three iterations of Gauss Newton to get 170(3). What is 179(3) (a numerical value)