sdv-dev/CTGAN
A Conditional GAN implementation that learns from real tabular data to generate high-fidelity synthetic datasets.
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CTGAN is part of the Synthetic Data Vault project and provides deep learning based generators for creating synthetic tabular data. It uses conditional generative adversarial networks to model the distribution of real data and produce synthetic records that preserve statistical properties. The tool is commonly used for data augmentation, testing database applications, and sharing datasets while preserving privacy.
Frequently asked
- What is sdv-dev/CTGAN?
- A Conditional GAN implementation that learns from real tabular data to generate high-fidelity synthetic datasets.
- Is CTGAN open source?
- Yes — sdv-dev/CTGAN is an open-source project tracked on heatdrop.
- What language is CTGAN written in?
- sdv-dev/CTGAN is primarily written in Python.
- How popular is CTGAN?
- sdv-dev/CTGAN has 1.6k stars on GitHub.
- Where can I find CTGAN?
- sdv-dev/CTGAN is on GitHub at https://github.com/sdv-dev/CTGAN.