AI Glossary
Data Augmentation
What is Data Augmentation?
Techniques used to artificially expand training datasets by creating modified versions of existing data — for example, rotating images, paraphrasing sentences, or adding noise. Data augmentation improves model robustness and reduces overfitting without requiring the collection of entirely new training data.
Example in practice
A team training an AI to classify customer sentiment from short feedback snippets might paraphrase each labelled example five ways — using data augmentation to build a larger, more varied training set without manual collection.
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