An opinionated list of Python frameworks, libraries, tools, and resources.

A collection of simple python mini projects to enhance your python skills

FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs o…

An open-source framework for machine learning and other computations on decentralized data.

Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)

Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data

基于树莓派的智能家居控制平台 微信服务端 发布版

原理解析及代码实战，推荐算法也可以很简单 🔥 想要系统的学习推荐算法的小伙伴，欢迎 Star 或者 Fork 到自己仓库进行学习🚀 有任何疑问欢迎提 Issues，也可加文末的联系方式向我询问！

Everything you want about DP-Based Federated Learning, including Papers and Code. (Mechanism: Laplace or Gaussian, Dataset: femnist, shakespeare, mnist, cifar-10 and fashion-mnist. )

Differentially private federated learning: A systematic review (ACM Survey); Adap dp-fl: Differentially private federated learning with adaptive noise (TrustCom'2022)

Backdoors Framework for Deep Learning and Federated Learning. A light-weight tool to conduct your research on backdoors.

元豚科技 - 基于日志安全分析做切入，做最好用的「云原生安全运维工作台」

Code for paper "Adaptive Federated Learning in Resource Constrained Edge Computing Systems"

DBA: Distributed Backdoor Attacks against Federated Learning (ICLR 2020)

Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470

A Simulator for Privacy Preserving Federated Learning

Privacy-Preserving Deep Learning via Additively Homomorphic Encryption

外包项目：网络安全日志采集及威胁风险分析SOC

Including common test models for federated learning, like CNN, Resnet18 and lstm, controlled by different parser.

MPC Secure Multiparty Computation. A three-party secret-sharing-based vertical federated learning setting. The data are vertically partitioned in two parties. A semi-honest third party is leveraged…

This is an implementation for paper "A Hybrid Approach to Privacy Preserving Federated Learning" (https://arxiv.org/pdf/1812.03224.pdf)