synthetic-data-generation

Synthetic data generation is useful for scenarios where real data is scarce, sensitive, or expensive to obtain. Techniques include simulations and generative models like GANs. A common misconception is that synthetic data is always inferior to real data; in many cases, well-crafted synthetic data can be as valuable and sometimes even more useful, especially for testing and training purposes.