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Fraud-Detection-Dynamics

Fraud Detection Dynamics is a machine learning system that uses advanced algorithms to identify fraudulent transactions in real-time

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

You will need the following software to run Fraud Detection Dynamics:

Python 3.6 or higher TensorFlow 2.0 or higher scikit-learn 0.23 or higher Installation

  • Clone the repository to your local machine: https://github.com/AnthonyByansi/Fraud-Detection-Dynamics.git
  • Navigate to the project directory: cd fraud-detection-dynamics
  • Install the required Python packages: pip install -r requirements.txt
  • Run the model training script: python train.py
  • Run the model evaluation script: python eval.py

Deployment

To deploy Fraud Detection Dynamics in a production environment, you will need to set up a server and run the model as a service. The exact steps for doing this will depend on your infrastructure and preferences.

Contributing

We welcome contributions to Fraud Detection Dynamics! If you have an idea for a new feature or a bug fix, please open a pull request.

License

Fraud Detection Dynamics is licensed under the MIT License. See LICENSE for details.