Why does L1 regularization encourage coefficients to shrink to zero? Introduction Regularization is a common method for dealing with overfitting in Machine Learning (ML). The simplest and most widely used methods are L1 (Lasso) and L2 (Ridge). The L1 and L2 regularizations are well covered in numerous tutorials and books. However, I could not find any good geometric or intuitive explanation of why…