There are 118 repositories under federated-learning topic.
A curated list of references for MLOps
An Industrial Grade Federated Learning Framework
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 on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.
A unified framework for privacy-preserving data analysis and machine learning
FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)
An easy-to-use federated learning platform
Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data
A PyTorch Implementation of Federated Learning http://doi.org/10.5281/zenodo.4321561
算法刷题指南、Java多线程与高并发、Java集合源码、Spring boot、Spring Cloud等笔记,源码级学习笔记后续也会更新。
A flexible Federated Learning Framework based on PyTorch, simplifying your Federated Learning research.
An open framework for Federated Learning.
All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.
Awesome Multitask Learning Resources
Complete-Life-Cycle-of-a-Data-Science-Project
A Privacy-Preserving Framework Based on TensorFlow
Federated Learning Benchmark - Federated Learning on Non-IID Data Silos: An Experimental Study (ICDE 2022)
resources about federated learning and privacy in machine learning
:books: :eyeglasses: A collection of research papers, codes, tutorials and blogs on Federated Computing/Learning.
Manage federated learning workload using cloud native technologies.
Handy PyTorch implementation of Federated Learning (for your painless research)
A curated list of awesome Distributed Deep Learning resources.
FedScale is a scalable and extensible open-source federated learning (FL) platform.
Infrastructures™ for Machine Learning Training/Inference in Production.
Simulate a federated setting and run differentially private federated learning.