What are synthetic data generation techniques, and how are they used to augment training datasets for machine learning models?

Synthetic data generation techniques create artificial data samples that mimic the distribution of real-world data. These techniques, such as generative models, data augmentation, and domain adaptation, are used to address data scarcity, imbalance, and privacy concerns in machine learning tasks.