 NVFlare
 NVFlare 
 Federated ML platform
 An extensible Python SDK for building secure and private machine learning applications in a federated paradigm
NVIDIA Federated Learning Application Runtime Environment
658 stars
 21 watching
 182 forks
 
Language: Python 
last commit: 11 months ago   decentralizedfederated-analyticsfederated-computingfederated-learningpetprivacy-protectionpython 
 Related projects:
| Repository | Description | Stars | 
|---|---|---|
|  | Provides tools and APIs for designing, scheduling, and running federated machine learning jobs in a secure and efficient manner. | 3 | 
|  | A Python framework for collaborative machine learning without sharing sensitive data | 738 | 
|  | A platform for conducting high-performance federated learning simulations in Python. | 185 | 
|  | A federated learning platform with tools and datasets for scalable and extensible machine learning experimentation | 390 | 
|  | An open source framework for collaborative machine learning with data distributed across multiple institutions. | 891 | 
|  | A particle-based simulation library for real-time applications | 675 | 
|  | An implementation of heterogeneous federated learning with parallel edge and server computation | 17 | 
|  | A comprehensive platform for federated learning, providing an event-driven architecture and flexible customization for various tasks in academia and industry. | 1,335 | 
|  | A federated learning platform for computer vision tasks using PaddleFL and PaddleDetection | 112 | 
|  | A flexible framework for distributed machine learning where participants train local models and collaboratively optimize them without sharing data | 743 | 
|  | A toolbox for building and training deep neural networks in Matlab | 70 | 
|  | This project enables personalized federated learning with inferred collaboration graphs to improve the performance of machine learning models on non-IID (non-independent and identically distributed) datasets. | 26 | 
|  | An all-in-one web-based IDE for machine learning and data science | 3,446 | 
|  | An implementation of a federated learning algorithm for handling heterogeneous data | 6 | 
|  | An approach to heterogeneous federated learning allowing for model training on diverse devices with varying resources. | 61 |