L1 and L2 regularization: Regularization techniques that add a penalty term to the loss function to discourage the model from having large weights. L1 regularization is also known as Lasso regularization, and it adds the absolute value of the weights to the loss function, while L2 regularization, also known as Ridge regularization, adds the square of the weights to the loss function.