Federated Prognos Chronos – A federated learning framework for time-series forecasting.
📖 Documentation: https://fedproc.readthedocs.io/
FedProC is a comprehensive federated learning framework designed specifically for time-series forecasting tasks. It enables distributed machine learning across multiple clients while preserving data privacy.
- 🔒 Privacy-Preserving: Keeps data local while enabling collaborative learning
- 📈 Time-Series Focused: Optimized for forecasting tasks
- 🚀 Scalable: Supports multiple clients and strategies
- 🧩 Modular: Easy to extend with custom models and strategies
Get started with FedProC in just a few steps:
- Installation - Set up your environment
- Usage - Run your first experiment
- Strategies - Choose your federated learning strategy
- Installation - Installation guide and requirements
- Usage - Basic usage and examples
- Strategies - Available federated learning strategies
- Datasets - Supported datasets and data preparation
- Models - Available models and architectures
- Losses - Loss functions and metrics
- Schedulers - Learning rate schedulers
- Customization - Extending the framework
- Code Formatting - Development guidelines
- Analysis - Results analysis
We welcome contributions! Please see our contributing guidelines for more information.
This project is licensed under the MIT License - see the LICENSE file for details.