Linear Regression and Regularization: A Developer's Guide

This article explains linear regression, ordinary least squares, and the five key assumptions for valid models. It covers multicollinearity detection using VIF and introduces regularization techniques like Ridge and Lasso to prevent overfitting. The piece includes practical Python code examples for implementation.