Discover the fundamentals of Ridge Regression, a powerful biased regression technique for handling multicollinearity and overfitting. Learn its canonical form, key differences from Lasso Regression (L1 vs L2 regularization), and why it’s essential for robust predictive modeling. Perfect for ML beginners and data scientists! Introduction In cases of near multicollinearity, the Ordinary Least Squares (OLS) estimator may perform worse compared to non-linear or biased estimators.