Data Augmentation

The practice of artificially expanding a training dataset by creating modified versions of existing data points, for example flipping or rotating images, or paraphrasing sentences. It helps models generalize better by exposing them to more variation without the cost of collecting new data.
See also: training data, overfitting, data preprocessing.