In a previous post, I presented (generalized) linear regression from a linear algebra point of view (namely, the “normal equations”) and in this post, I discuss yet another take on the problem, this time using gradient descent.
Gradient descent isn’t particularly fascinating for this particular task (as we know closed, analytical expressions for obtaining the parameters), but linear regression is the simplest example of gradient descent I could come up with without being completely trivial.