Guide
Synthetic Data & Augmentation Primer
Practical guide to when and how to use synthetic data for scarce or sensitive datasets: generation approaches, labeling propagation, quality checks, evaluation strategies against held-out real data, governance, and a compact experimental workflow teams can try.
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