Web Reference: Mar 3, 2026 · Data augmentation helps machine learning models perform better by making the most of existing data. It prevents overfitting, improves accuracy, and creates diversity in training data, which is crucial when datasets are small or imbalanced. Overview This tutorial demonstrates data augmentation: a technique to increase the diversity of your training set by applying random (but realistic) transformations, such as image rotation. You will learn how to apply data augmentation in two ways: Data augmentation improves machine learning model optimization and generalization. In other words, data augmentation can reduce overfitting and improve model robustness. 2 That large, diverse datasets equal improved model performance is an axiom of machine learning.
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