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Federated Learning for Privacy-Preserving Financial Data Generation

Overview

This documentation covers the implementation and usage of a federated learning system for generating synthetic financial data with privacy preservation using RAG (Retrieval-Augmented Generation).

Quick Start

Architecture

The system consists of three main components:

  1. Federated Learning Framework
  2. Privacy-Preserving Data Generation
  3. RAG Integration

Components

  • Client Implementation
  • Server Coordination
  • RAG System
  • Privacy Management
  • Data Handling

Contributing

Please read our Contributing Guidelines for details on submitting pull requests.

License

This project is licensed under the MIT License - see the LICENSE file for details.