# Data Augmentation

> Source: https://sukruyusufkaya.com/en/glossary/data-augmentation
> Updated: 2026-05-13T19:59:43.353Z
> Type: glossary
> Category: derin-ogrenme
**TLDR:** A regularization approach that improves generalization by expanding training data through meaningful transformations.

<p>Data augmentation is one of the most effective regularization tools in deep learning, especially when labeled data is limited. Rotations, crops, color perturbations, noise injection, or semantics-preserving text transformations may be applied. This helps the model become more robust to minor variations in the data. Because representation learning is so data-dependent, augmentation can be as important as the model architecture itself.</p>