FedERA

FedERA is a highly dynamic and customizable framework that can accommodate many use cases with flexibility by implementing several functionalities over different federated learning algorithms, and essentially creating a plug-and-play architecture to accommodate different use cases.

Check out the Overview of FedERA section for further information, including how to Installation the project.

Note

This project is under active development.

Contents

• Overview of FedERA
  • Introduction
  • Overview
• Installation
  • Install the package
  • FedERA with Docker
• Tutorials
  • Running the Server and Clients
  • Federated Learning Algorithms
  • Datasets
  • Models
  • Data Distribution
  • Carbon Emissions
  • Encryption
• Contribution to FedERA
  • Reporting bugs
  • Contributing to FedERA
  • Pull Request Checklist
• Reference
• API Reference
  • federa
  • scaffold
  • fedadam
  • fedavgm
  • fedadagrad
  • fedavg
  • mimelite
  • mime
  • feddyn
  • fedyogi

Contacts

Contact the FedERA development team through Github issues or email:

• Development Team: federa.team@gmail.com