: First, regularization was the technique which helps to solve the fitting problem in Machine Learning. Regularization inclines into spread error among all the terms, while L1 was more binary, with most variables either being assigned a 1 or 0 in weighting. This corresponds into setting a Laplacian prior on the terms, while L2 corresponds into a Gaussian prior.