CODE: %in this exercise, you will investigate linear regression using gradient descent % and the normal equations %This is a training set of housing prices in Portland, Oregon, where %y are the prices and the inputs $x are the living area and the number of bedrooms. %we will use only living area in this assigment % initialize samples of x and y training dataset % x2 = load('ex3x.dat'); y = load('ex3y.dat'); %house cost x=x2(:,1); %only living area m = length(y); % store the number of training examples x = [ones(m, 1), x]; % Add a column of ones to x %the area values from your training data are actually in the second column of x %calculate parametar w using normal equation %your code here % %w= %code end disp("w0 w1"),disp(wn); #predict the house price with 1650sf disp("house prediction for 1650s, normal eq:"),disp([1,1650]*wn); yp=x*wn; #plot data and regression line figure % open a new figure window # plot your training set (and label the axes): plot(x(:,2),y,'o'); ylabel('house cost') xlabel('house sf') hold plot(x(:,2),yp,'-'); 

How do you modify the code to calculate linear estimator using normal equation, and then use the parameters to calculate price of the house with 1650sf I am stuck please help Step by step to understanding. Please provide a finished code.