Data Catalog

Data augmentation is a technique used in artificial intelligence to artificially expand a dataset by generating new, varied samples from existing data. This involves applying transformations such as rotations, scaling, cropping, or noise addition, which help improve model robustness, reduce overfitting, and enhance generalization, especially in scenarios with limited data like image recognition, speech processing, and natural language tasks.