A curated list of references for MLOps

Perform data science on data that remains in someone else's server

Flower: A Friendly Federated AI Framework

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

Master Federated Learning in 2 Hours—Run It on Your PC!

Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond

FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai

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

An easy-to-use federated learning platform

A PyTorch Implementation of Federated Learning

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

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。

[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification

联邦学习

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。

NVIDIA Federated Learning Application Runtime Environment

No description available

An Open Framework for Federated Learning.

A flexible Federated Learning Framework based on PyTorch, simplifying your Federated Learning research.

A collection of Google research projects related to Federated Learning and Federated Analytics.

OpenHuFu is an open-sourced data federation system to support collaborative queries over multi databases with security guarantee.

All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. ACM Computing Surveys, 2026.

Benchmark of federated learning. Dedicated to the community. 🤗

Awesome Multitask Learning Resources

Complete-Life-Cycle-of-a-Data-Science-Project

Everything about Federated Learning (papers, tutorials, etc.) -- 联邦学习

An experimental platform for federated learning.