1-Change this code from Matlab to Phython: initial_theta = zeros (size (X, 2), 1); 46 47 48 lambda = 1; options = optimoptions (@ fminunc, 'Algorithm', 'Quasi-Newton','Gradobj', 'on', [theta, J,...

Extracted text: 1-Change this code from Matlab to Phython: initial_theta = zeros (size (X, 2), 1); 46 47 48 lambda = 1; options = optimoptions (@ fminunc, 'Algorithm', 'Quasi-Newton','Gradobj', 'on', [theta, J, exit_flag] = fminunc (@ (t) (costFunctionReg (t, X, y, lambda)), initial_theta, options); plotDecisionBoundary (theta, X, y); 49 'MaxIter', 1000); 50 51 52 hold on; title (sprintf ('lambda = %g', lambda)) xlabel ('Microchip Test 1') ylabel ('Microchip Test 2') legend ('y = 1', 'y = 0', 53 54 55 56 'Decision boundary') 57 hold off; p = predict (theta, X); fprintf('Train Accuracy: %f\n', mean (double (p == y)) * 100); 58 59