{"id":21423433,"url":"https://github.com/nafisalawalidris/fraud-detection-with-supervised-learning","last_synced_at":"2025-07-14T08:31:23.231Z","repository":{"id":259916327,"uuid":"866257949","full_name":"nafisalawalidris/Fraud-Detection-with-Supervised-Learning","owner":"nafisalawalidris","description":"This repository contains a basic fraud detection system utilising supervised learning techniques to identify potentially fraudulent credit card transactions. 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Utilising supervised learning techniques, this project serves as a foundational model for understanding and addressing credit card fraud issues faced by financial institutions.\n\n## If you find this project useful, please consider giving it a star ⭐ on GitHub. Contributions are also welcome!\n\n![alt text](\u003cFraud Detection.png\u003e)\n\n## **Table of Contents**\n\n- [Technologies Used](#technologies-used)\n- [Getting Started](#getting-started)\n- [Installation](#installation)\n- [Usage](#usage)\n- [Features](#features)\n- [Contributing](#contributing)\n- [License](#license)\n- [Contact](#contact)\n\n## **Technologies Used**\n\n- **Python**: Programming language used for development.\n- **FastAPI**: Framework for building the API.\n- **Scikit-learn**: Machine learning library used for model training.\n- **Pandas**: Data manipulation library.\n- **NumPy**: Library for numerical operations.\n- **Joblib**: Library for model serialisation.\n\n## **Getting Started**\n\nTo get a local copy of this project up and running, follow these steps:\n\n### **Installation**\n\n1. Clone the repository:\n```bash\n   git clone https://github.com/nafisalawalidris/Fraud-Detection-with-Supervised-Learning.git\n```\n\n2. Navigate to the project directory:\n```bash\ncd Fraud-Detection-with-Supervised-Learning\n```\n\n3. Create a virtual environment:\n```bash\npython -m venv fraud_detection_env\n```\n\n4. Activate the virtual environment:\n- On Windows:\n```bash\n.\\fraud_detection_env\\Scripts\\activate\n```\n- On macOS/Linux\n```bash\nsource fraud_detection_env/bin/activate\n```\n\n5. Install the required packages:\n```bash\npip install -r requirements.txt\n```\n\n## **Usage**\n1. Run the FastAPI server:\n```bash\nuvicorn main:app --reload\n```\nThen open your browser and go to http://localhost:8501.\n\n2. Send a POST request to the /predict endpoint with transaction data in the following format:\n```bash\n{\n    \"Time\": 123456,\n    \"V1\": 0.0,\n    \"V2\": 1.0,\n    ...\n    \"Amount\": 100.00\n}\n```\n3. Receive a response with fraud prediction and probability:\n```bash\n{\n    \"fraud_prediction\": true,\n    \"fraud_probability\": 0.95\n}\n```\n\n## **Features**\n- Simple and effective fraud detection using supervised learning techniques.\n- RESTful API built with FastAPI for easy integration.\n- Detailed logging of predictions and transactions.\n- Well-structured codebase that allows for easy modifications and enhancements.\n\n## **Contributing**\nContributions are welcome, If you have suggestions for improvements or want to contribute to this project, please fork the repository and create a pull request.\n\n### **How to Contribute**\n```bash\nFork the repository.\nCreate a new feature branch (git checkout -b feature-name).\nCommit your changes (git commit -m 'Add some feature').\nPush to the branch (git push origin feature-name).\nOpen a pull request.\n```\n\n## **License**\nhis project is licensed under the MIT License. See the LICENSE file for more information.\n\n## **Contact**\nFor any inquiries or feedback, please contact me at https://nafisalawalidris.github.io/13/.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnafisalawalidris%2Ffraud-detection-with-supervised-learning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnafisalawalidris%2Ffraud-detection-with-supervised-learning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnafisalawalidris%2Ffraud-detection-with-supervised-learning/lists"}