Regularization, Overfitting, Dropout Regularization, Early Stopping, Elastic Net.
Net? In many scikit-learn models L2 is the default (see LogisticRegression and SupportVectorMachines). This is for a reason: L1 tends to shrink some of the weight coefficients to zero, which means the features are removed from te model. So L1 regularization is more useful for feature selection. To