Machine Learning, Artificial Intelligence, Deep Learning, Data Science, Mathematics.
L1 and L2 regularization hinges on the specific needs of the dataset and the desired balance between bias and variance. While L1 is preferable for models requiring feature selection and simplicity, L2 is more suitable for models where retaining all features is important, and a balanced contribution