why gradient descent when we can solve linear regression analytically

Question

what is the benefit of using Gradient Descent in the linear regression space? looks like the we can solve the problem (finding theta0-n that minimum the cost func) with analytic

Answer 1

Other reason is that gradient descent is immediately useful when you generalize linear regression, especially if the problem doesn't have a closed-form solution, like for example in Lasso (which adds regularization term consisting on sum of absolute values of weight vector).