SDV

Synthetic data generation for tabular data

View on GitHub↗Upstream sdv-dev/SDV↗

Builder

sdv-dev

sdv-dev • individual

Stars

3,457

Using upstream star count

Forks

415

Using upstream fork count

Open Issues

Activity Score

0/100

0 commits in 30d

Created

May 11, 2018

Project creation date

README Summary

SDV (Synthetic Data Vault) is a Python library for generating synthetic tabular data that preserves the statistical properties and relationships of the original dataset. It provides various machine learning models and techniques to create realistic synthetic data for testing, privacy protection, and data augmentation purposes. The library supports multiple data types including numerical, categorical, and datetime columns with customizable constraints and relationships.

AI Dev Skills

Unmapped

Generative ModelingTabular Data SynthesisStatistical Data ModelingPrivacy-Preserving Machine LearningBayesian NetworksCopula ModelsDeep Learning for Tabular DataData AugmentationDifferential Privacy

Tags

Generative ModelingTabular Data SynthesisStatistical Data ModelingPrivacy-Preserving Machine LearningBayesian NetworksCopula ModelsDeep Learning for Tabular DataData AugmentationDifferential PrivacyCloud APIInsurancePrivacy-compliant data sharingPrivacy-Preserving AIData augmentation for machine learningAI SafetyResearch dataset anonymizationSelf-hostedRetail AnalyticsHealthcareSynthetic Data GenerationFinTechOn-premiseTabularML model testing with synthetic datasetsSoftware testing with realistic test dataTelecommunicationsRegulatory compliance for sensitive dataPython

Recent Activity

Updated 25 days ago

7 Days

30 Days

90 Days

Quality

production

Quality: high
Maturity: production

PM Skills

Product Discovery

Languages

Python100.0%

Timeline

Project created: May 11, 2018
Forked: Mar 22, 2026
Your last push: 25 days ago
Upstream last push: 7 days ago
Tracked since: Mar 19, 2026

Similar Repos

pgvector cosine similarity · $0

Loading…

SDV