$\backslash$table$[[$longitude$,$latitude,housing$\_$median$\_$age,total$\_$rooms,total$\_$bedrooms,population,households,median$\_$income,median$\_$house$\_$value,ocean$\_$proximity$],[-122\mathrm{.}23,37\mathrm{.}88,41\mathrm{.}0,880\mathrm{.}0,129\mathrm{.}0,322\mathrm{.}0,126\mathrm{.}0,8\mathrm{.}3252,452600\mathrm{.}0,$NEAR BAY$],[-122\mathrm{.}22,37\mathrm{.}86,21\mathrm{.}0,7099\mathrm{.}0,1106\mathrm{.}0,2401\mathrm{.}0,1138\mathrm{.}0,8\mathrm{.}3014,358500\mathrm{.}0,$NEAR BAY$],[-122\mathrm{.}24,37\mathrm{.}85,52\mathrm{.}0,1467\mathrm{.}0,190\mathrm{.}0,496\mathrm{.}0,177\mathrm{.}0,7\mathrm{.}2574,352100\mathrm{.}0,$NEAR BAY$],[-122\mathrm{.}25,37\mathrm{.}85,52\mathrm{.}0,1274\mathrm{.}0,235\mathrm{.}0,558\mathrm{.}0,219\mathrm{.}0,5\mathrm{.}6431,341300\mathrm{.}0,$NEAR BAY$]]$Using scikit$-$learn and it$$s dependencies write a Python program that creates a linear regression model to predict median$\_$house$\_$value from the Maryland housing data given in the above problem $($#$2).$ The program should perform the following: a$.$ Perform necessary pre$-$processing on the given data and save processed data into housing$\_$data.csv $2$ b$.$ Create and train linear regression model for the prediction to be made