What are the differences between synthetic data and real data?

What are the differences between synthetic data and real data?

Synthetic data is artificially generated, while real data is collected from actual events or observations. Synthetic data can be used to augment real datasets, especially when real data is scarce or sensitive.

What are the advantages of using synthetic data?

Synthetic data can help in protecting privacy, reducing bias, and providing more diverse training examples for machine learning models.

Are there any downsides to using synthetic data?

Yes, synthetic data may not capture all the complexities of real-world scenarios, which can lead to less effective models if not used carefully.

In what scenarios is synthetic data preferred over real data?

Synthetic data is preferred in situations where real data is limited, expensive to obtain, or involves privacy concerns, such as healthcare or finance.