Fraud Detection Dynamics is a machine learning system that uses advanced algorithms to identify fraudulent transactions in real-time
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
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
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.
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.
Fraud Detection Dynamics is licensed under the MIT License. See LICENSE for details.