Differential Privacy Python Packages

interpret-core

Fit interpretable models. Explain blackbox machine learning.

interpret

Fit interpretable models. Explain blackbox machine learning.

opacus

Training PyTorch models with differential privacy

opendp

The core library of differential privacy algorithms powering the OpenDP Project.

dp-accounting

Google's differential privacy libraries.

smartnoise-sql

Tools and service for differentially private processing of tabular and relational data

diffprivlib

Diffprivlib: The IBM Differential Privacy Library

mostlyai

Synthetic Data SDK ✨

mostlyai-engine

Synthetic Data Engine 💎

gretel-synthetics

Synthetic data generators for structured and unstructured text, featuring differentially private learning.

python-dp

The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy

tmlt-core

Tumult's differential privacy primitives

secretflow

A unified framework for privacy-preserving data analysis and machine learning

smartnoise-synth

Tools and service for differentially private processing of tabular and relational data

riskcal

Measure and calibrate operational privacy risks for differentially private algorithms.

secretflow-lite

SecretFlow Lite

dp-sequential-events

Privatized

diffpriv

A Differential Privacy Package

opendp-smartnoise-core

Python language bindings for smartnoise-core.

tmlt-analytics

Tumult Analytics is a Python library for privately computing aggregate queries on tabular data. It is built atop the Tumult Core library.

aisdc

Tools for the statistical disclosure control of machine learning models

trasgodp

Local differential privacy mechanisms

redco

No description available

dp-cgans

A library to generate synthetic tabular or RDF data using Conditional Generative Adversary Networks (GANs) combined with Differential Privacy techniques.