Search 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.

diffprivlib

Diffprivlib: The IBM Differential Privacy Library

smartnoise-sql

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

mostlyai

Synthetic Data SDK ✨

secretflow

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

gretel-synthetics

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

mostlyai-engine

Synthetic Data Engine 💎

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-lite

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

dp-sequential-events

Differential privacy for sequential event logs, anonymizing case IDs and timestamps while preserving statistical properties.

opendp-smartnoise-core

Deprecated. Please use the OpenDP library: https://github.com/opendp/opendp

tmlt-analytics

Tumult's differential privacy analytics API

riskcal

Measure and calibrate operational privacy risks for differentially private algorithms.

diffpriv

A python package for differential privacy and encryption.

redco

NAACL '24 (Best Demo Paper RunnerUp) / MlSys @ NeurIPS '23 - RedCoast: A Lightweight Tool to Automate Distributed Training and Inference

aisdc

Tools for the statistical disclosure control of machine learning models

pure-ldp

Python package for simple implementations of state-of-the-art LDP frequency estimation algorithms. Contains code for our VLDB 2021 Paper.

dp-cgans

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