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Data Augmentation
A technique used in machine learning to artificially increase the size of a training dataset by applying various transformations to the existing data, such as rotation, scaling, or cropping, in order to improve the model's generalization and performance. Data augmentation helps prevent overfitting and improves the robustness of machine learning models.