b$)$ Suppose you have been given a large dataset with $n=20,00,000$ instances and $m($# of features$)=3000$ for each instance. You are asked to use multivariate linear regression to fit the $$ parameters to our data. Which approach would you prefer, gradient descent or closed form solution and Why?

$[3]$