Lasso Regression, Ridge Regression, L1 Regularization, L2 Regularization.
to the error function and this penalty is the sum of absolute value of weights. lambda is the tuning parameter which decides how much we want to penalize the model J(theta) is the cost function Ridge Regression (L2 Regularization) It adds a penalty to the error function and this penalty is the