Is Synthetic Data a Reliable Option for Training Machine Learning Models?

Synthetic data is the product of generative AI models that learn how real-world data behaves, mimicking relationships and trends without coming from real-world events or people.

Synthetic data generation methods include statistical distribution, model-based generation using machine learning models, and deep learning methods like generative adversarial networks (GANs).

Regardless of the specific method, synthetic data behaves similarly to real-world data but does not reflect actual people, places, or events, providing an advantage in terms of privacy.

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