Data Augmentation

Data augmentation is a technique used to artificially expand a training dataset by creating modified versions of existing data. For images, this might involve rotating, flipping, or cropping original pictures to generate new, varied examples. This helps models generalize better and reduces overfitting, especially when original datasets are small.