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AI Data Preparation & Feature Engineering › Data Augmentation

How does Data Augmentation work

Beginner

Answer

The original data is transformed in ways that preserve its meaning, such as rotating an image slightly or replacing a word with a synonym, to increase the variety seen during training.
Real-world example A team training an image model uses data augmentation to flip and rotate photos, effectively increasing the size of their training dataset.

Common follow-ups: What is AI Data Preparation & Feature Engineering, How is Data Augmentation evaluated in practice, What tools are commonly used for Data Augmentation

AI Data Preparation & Feature Engineering topics: Data Cleaning for AI Models Handling Missing Data Feature Scaling & Normalization
All 7 Data Augmentation questions