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

I saw a very good answer from https://stats.stackexchange.com/questions/23128/solving-for-regression-parameters-in-closed-form-vs-gradient-descent

Basically, the reasons are:

1.For most nonlinear regression problems there is no closed form solution.

2.Even in linear regression (one of the few cases where a closed form solution is available), it may be impractical to use the formula. The following example shows one way in which this can happen.