Shypd.aiThe largest open index of AI toolsSDV is an open-source synthetic data generation tool for tabular data. It uses machine learning to create synthetic datasets that emulate real data patterns while preserving privacy.
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The Synthetic Data Vault (SDV) is a Python library designed for generating tabular synthetic data. It employs various machine learning algorithms, from classical statistical methods like GaussianCopula to deep learning methods such as CTGAN, to learn patterns from real data and replicate them in synthetic datasets. SDV supports generating data for single tables, multiple connected tables, or sequential tables. Users can evaluate and visualize the quality of synthetic data against real data, diagnose problems, and generate quality reports. The library also offers features for preprocessing, anonymizing, and defining logical constraints to control data processing and improve synthetic data quality. SDV is part of The Synthetic Data Vault Project by DataCebo, providing a comprehensive solution for synthetic data generation and evaluation.
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