2- Multivariable Linear Regression In this case both features re considered to build a Linear Regression. y=w2x2+w1x1+w0 Where x1 and x2 correspond respectively to the features Area and number of rooms. a) Scaling of the data according to the two following steps - Subtract the mean value of each feature from the dataset. - After subtracting the mean, additionally scale (divide) the feature values by their respective standard deviations. b) Give the normal equations that compute the linear regression parameter vector W=(w0,w1,w2)T (fill the matrix Xb and the vector Y by the appropriate values)