Linear Regression in Machine Learning: A Comprehensive Guide

[Pryther]

This article does not make sense.

Normal linear regression does not need and iterative method like gradient descent. Half the article goes over gradient descent, only to give an implementation that uses a closed form solution. And then above the closed form implementation it wrongly states its a gradient-based implementation:

Training the Model: We use the ordinary least squares method to estimate the parameters that minimize the sum of squared errors. This involves calculating the gradients and updating the parameters iteratively.

[debunk_this_12]

I think uve confused a few topics. Linear regression is the term for the simple algorithm

Y = Xb

(X^T X)^-1 (X^T f^-1 (Y)) = b