Machine Learning, Artificial Intelligence, Deep Learning, Data Science, Mathematics.
promotes sparsity. This property is particularly useful in high-dimensional datasets where feature selection is crucial. By driving certain coefficients to zero, L1 regularization simplifies the model and enhances interpretability by identifying the most relevant features. In contrast, L2