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Real-Time Fraud Detection API Documentation

Welcome to the central documentation for the Real-Time Fraud Detection API project. This site provides in-depth information on the project's architecture, business goals, and operational procedures.

This project is a production-ready machine learning system designed to classify mobile financial transactions as fraudulent or legitimate, with a focus on MLOps best practices.

To get started, please use the navigation panel or the links below:

  • Usage Guide: Learn how to run, test, and manage the project.
  • Business Context: Understand the business problem, goals, and monetization model behind the project.
  • Project Files: Explore the project's structure and get a description of key files and directories.
  • Logging: Get a detailed overview of the project's structured logging system.
  • Testing Strategy: Learn about the testing philosophy, tools, and procedures used in the project.

For a quick guide on how to get the development environment up and running, please see the repository's README.md file on GitHub.