SVM L1 (Support Vector Machine with L1 regularization) is a machine learning algorithm that is commonly used for classification and regression tasks. It is known for its ability to handle large datasets and its effectiveness in handling high-dimensional feature spaces. The L1 regularization term in SVM L1 helps to improve the model's ability to select important features and reduce the impact of irrelevant or noisy features. Overall, SVM L1 is a powerful tool in the field of machine learning and can be applied to a wide range of problems.