how to solve these parts

2. We want to nd the optimal parameter w. E R2 for linear rega'ession with weighted mean equated error and the data below: 2 1 X: 3 4 5 , y= 7 , weight k= 4 , W0: 0 3 2 6 3 2 0 That is, we want to nd w. such that N . 1 W. = argmmw Zia-(\"dict- v.02 i=1 where k,- is the weight for i-th data sample. (a) Derive a gradient descent algorithm (steepest descent) with the learning rate 0005, and continute the steps until t=5 by using your algorithm and initial guess W0 above. That is, you have to compute and show W1 for 1 S t S 5. (b) Derive the closed form solution and nd W. with it