(a) Use Python to compute the weight vector w = [w0,w1,w2]T for linear regression of N input data points (xi,yi) that minimizes the sum of squared error (wTxi yi)2 The input data are x1=(1,3,2)T y1 = 3 x2=(1,2,2)T y2 = 1 x3=(1,1,-1)T y3 = -1 x4=(1,-1,-3)T y4= -3

(b) Use the linearRegression module in Python package sklearn to find w for linear regression. Steps of the python code and intermediate results are needed

Please do B