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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Synthetic data generation for tabular data
| Date | Stars |
|---|---|
| 2026-07-24 | 3530 |
| 2026-07-25 | 3530 |
| 2026-07-28 | 3530 |
| 2026-07-30 | 3530 |
| 2026-08-06 | 3530 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
35.0
growth rate 0.00%/day
<div align="center">
<br/>
<p align="center">
<i>This repository is part of <a href="https://sdv.dev">The Synthetic Data Vault Project</a>, a project from <a href="https://datacebo.com">DataCebo</a>.</i>
</p>
[](https://pypi.org/search/?c=Development+Status+%3A%3A+5+-+Production%2FStable)
[](https://pypi.python.org/pypi/SDV)
[](https://github.com/sdv-dev/SDV/actions/workflows/unit.yml?query=branch%3Amain)
[](https://github.com/sdv-dev/SDV/actions/workflows/integration.yml?query=branch%3Amain)
[](https://codecov.io/gh/sdv-dev/SDV)
[](https://pepy.tech/project/sdv)
[](https://docs.sdv.dev/sdv/demos)
[](https://forum.datacebo.com)
<div align="left">
<br/>
<p align="center">
<a href="https://github.com/sdv-dev/SDV">
<img align="center" width=40% src="https://github.com/sdv-dev/SDV/blob/stable/docs/images/SDV-logo.png"></img>
</a>
</p>
</div>
</div>
# Overview
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 algorithms to learn
patterns from your real data and emulate them in synthetic data.
## Features
:brain: **Create synthetic data using machine learning.** The SDV offers multiple models, ranging
from classical statistical methods (GaussianCopula) to deep learning methods (CTGAN). Generate
data for single tables, multiple connected tables or sequential tables.
:bar_chart: **Evaluate and visualize data.** Compare the synthetic data to the real data against a
variety of measures. Diagnose problems and generate a quality report to get more insights.
:arrows_counterclockwise: **Preprocess, anonymize and define constraints.** Control data
processing to improve the quality of synthetic data, choose from different types of anonymization
and define business rules in the form of logical constraints.
| Important Links | |
| --------------------------------------------- | ----------------------------------------------------------------------------------------------------|
| [![][Colab Logo] **Tutorials**][Tutorials] | Get some hands-on experience with the SDV. Launch the tutorial notebooks and run the code yourself. |
| :book: **[Docs]** | Learn how to use the SDV library with user guides and API references. |
| :orange_book: **[Blog]** | Get more insights about using the SDV, deploying models and our synthetic data community. |
| :busts_in_silhouette: **[DataCebo Forum]** | Discuss SDV features, ask questions, and receive help . |
| :computer: **[Website]** | Check out the SDV website for more information about the project. |
[Website]: https://sdv.dev
[Blog]: https://datacebo.com/blog
[Docs]: https://bit.ly/sdv-docs
[Repository]: https://github.com/sdv-dev/SDV
[License]: https://github.com/sdv-dev/SDV/blob/main/LICENSE
[Development Status]: https://pypi.org/search/?c=Development+Status+%3A%3A+5+-+Production%2FStable
[DataCebo Forum]: https://forum.datacebo.com
[Colab Logo]: hExcerpt of 9,865 characters
Read on GitHub
Andrew Montanez
426
Carles Sala · @precognit
355
Felipe Alex Hofmann · @datacebo · United States
199
192
Plamen Valentinov Kolev · @sdv-dev
164
Jose David Pérez Cañellas
159
SDV Team · @sdv-dev · United States
154
Frances Hartwell
130
Katharine Xiao
97
96
61
Roy Wedge
53
Gaurav Sheni · @datacebo · United States
49
23
11
10
Kalyan Veeramachaneni · MIT
8
7
4
Taylor Miller
2
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:2c540df1540214a2, topic:synthetic-data, desc:synthetic data, readme:synthetic data
matched fp:2c540df1540214a2, topic:deep-learning
matched fp:2c540df1540214a2, topic:gan