In machine learning, regularization is a method by which the ML model cost/error function is changed, to include an extra variable called the regularization hyperparameter. There are two basic types of regularization: L1-norm (lasso regression) and L2-norm (ridge regression). The Lasso regularization uses the L1 norm parameter. The lasso regularized cost function is calculated as … Read more