CTGAN is a collection of Deep Learning based synthetic data generators for single table data, which are able to learn from real data and generate synthetic data with high fidelity. If you're just getting started with synthetic data, we recommend installing the SDV library which provides user-friendly APIs for accessing CTGAN. The SDV library provides wrappers for preprocessing your data as well as additional usability features like constraints. When using the CTGAN library directly, you may need to manually preprocess your data into the correct format, for example, continuous data must be represented as floats. Discrete data must be represented as ints or strings. The data should not contain any missing values.

Features

  • Use the CTGAN standalone library
  • Use CTGAN through the SDV library
  • Continuous data must be represented as floats
  • Discrete data must be represented as ints or strings
  • The data should not contain any missing values
  • Currently, this library implements the CTGAN and TVAE models described in the Modeling Tabular data using Conditional GAN paper

Project Samples

Project Activity

See All Activity >

Follow CTGAN

CTGAN Web Site

Other Useful Business Software
Auth0 for AI Agents now in GA Icon
Auth0 for AI Agents now in GA

Ready to implement AI with confidence (without sacrificing security)?

Connect your AI agents to apps and data more securely, give users control over the actions AI agents can perform and the data they can access, and enable human confirmation for critical agent actions.
Start building today
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of CTGAN!

Additional Project Details

Programming Language

Python

Related Categories

Python Generative Adversarial Networks (GAN), Python Generative AI, Python Synthetic Data Generation Software

Registered

2023-03-21