A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
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Updated
May 25, 2024
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
An Industrial Grade Federated Learning Framework
A unified framework for privacy-preserving data analysis and machine learning
OpenHuFu is an open-sourced data federation system to support collaborative queries over multi databases with security guarantee.
THIS REPO IS NOT MAINTAINED ANYMORE. Please see https://codeberg.org/tenacityteam/tenacity for Tenacity, which is maintained.
基于区块链的符合W3C DID和Verifiable Credential规范的分布式身份解决方案
Privacy-Preserving Computing Platform 由密码学专家团队打造的开源隐私计算平台,支持多方安全计算、联邦学习、隐私求交、匿踪查询等。
Golang implementation of the PlatON protocol
Insomnium is a fast local API testing tool that is privacy-focused and 100% local. For testing GraphQL, REST, WebSockets and gRPC. This is a fork of Kong/insomnia
SPU (Secure Processing Unit) aims to be a provable, measurable secure computation device, which provides computation ability while keeping your private data protected.
A STARK-based ZKVM which aims to Programmable Scalability, Programmable Privacy
Kuscia(Kubernetes-based Secure Collaborative InfrA) is a K8s-based privacy-preserving computing task orchestration framework.
Go implementation of Waku v2 protocol
nGraph-HE: Deep learning with Homomorphic Encryption (HE) through Intel nGraph
Differential private machine learning
Privacy preserving voluntary Covid-19 self-reporting platform. Share your location history and status, get alerts you are in high risk areas and identify high risk regions
Android 1.0+ mini notification based audio player
Open source privacy-friendly analytics
Decentralized & federated privacy-preserving ML training, using p2p networking, in JS
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