How is synthetic data generated?

What is synthetic data and how is it generated?

Synthetic data is artificially generated data that mimics real data. It's created using algorithms and models.

What are the common methods used to generate synthetic data?

Common methods include data augmentation, generative adversarial networks (GANs), and simulation-based approaches.

Can synthetic data be used for training machine learning models?

Yes, synthetic data is often used to train machine learning models, especially when real data is scarce or sensitive.

Are there any limitations to using synthetic data?

Yes, limitations include potential biases in the generated data and the risk of not fully representing real-world scenarios.