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DeepBridge Synthetic

Tests codecov PyPI version Python 3.10+ License: MIT

Privacy-Preserving Synthetic Data Generation

Standalone Package - No Dependencies on DeepBridge!

This package can be used independently for synthetic data generation. It was extracted from DeepBridge v1.x to provide a focused, standalone solution. See Migration Guide if migrating from v1.x.

Installation

pip install deepbridge-synthetic

Quick Start

from deepbridge_synthetic import Synthesize

# Generate synthetic data
synthesizer = Synthesize(
    data=original_df,
    method='gaussian_copula'
)

synthetic_df = synthesizer.generate(n_samples=10000)

Features

  • Gaussian Copula: Statistical modeling for synthetic data
  • Privacy-Preserving: Generate data while protecting privacy
  • Quality Metrics: Evaluate synthetic data quality
  • Distributed Computing: Uses Dask for large datasets
  • Multiple Methods: Various generation algorithms

Documentation

Full documentation: https://deepbridge.readthedocs.io/en/latest/synthetic/

Related Projects

License

MIT License - see LICENSE

Metadata

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