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They build a generative AI model using your real data, and use it to create synthetic data. We recommend starting with GaussianCopulaSynthesizer for fast performance, good quality,%Single Table Data Evaluation As a final step to your synthetic data project, you can evaluate and visualize the synthetic data against the real data.$6 days ago · The Synthetic Data Vault (SDV) is a Python library designed to be your one-stop shop for creating tabular synthetic data. The SDV uses a variety of machine learning a!Sequential Data Modeling The SDV creates synthetic data using machine learning. A synthesizer is an object that you can use to accomplish this task.~Synthetic Data Creation Create synthetic data that matches the patterns in your real data — as well as other specifications that you have for your project.*Single table synthesizers can support multiple sampling needs. Sample Realistic Data Create large amounts of synthetic data that follow the same format and mathematical properties ^Sequential data represents ordered records, such as in a timeseries. The entire table may contain records for a single entity (such as a user or patient). Alternatively, your table