Data-Centric-AI-Community/ydata-synthetic
Synthetic data generators for tabular and time-series data
Implements multiple GAN architectures (CTGAN, WGAN-GP, DRAGAN) alongside a lightweight Gaussian Mixture option for CPU-friendly synthesis, all built on TensorFlow 2.0. Supports both tabular and sequential data through specialized models like TimeGAN and DoppelGANger, with optional Streamlit UI for low-code generation workflows. Includes conditional generation capabilities to handle imbalanced or biased datasets while preserving privacy.
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MIT
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Last pushed
Mar 02, 2026
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