Realistic Data Synthesis

Realistic Data Synthesis is a technique used to create artificial data that closely resembles real-world data. It involves generating new information that mimics typical patterns, structures, and relationships found in actual data sets. This process helps protect privacy, enable testing, or improve machine learning models without using sensitive or proprietary data directly. Essentially, it produces believable, fake data that can be used safely and effectively for research and development.