Devnetly/email-spam-classification

This repository contains a machine learning model for detecting spam emails using Natural Language Processing techniques and Semi-supervised learning, such as Label Propagation, Label Spreading and Self-Learning. The goal is to create an effective and efficient spam detection system that can classify emails as spam or non-spam with high accuracy.

Email Spam Classification

This repository contains a machine learning model for detecting spam emails using Natural Language Processing techniques and Semi-supervised learning, such as Label Propagation, Label Spreading and Self-Learning. The goal is to create an effective and efficient spam detection system that can classify emails as spam or non-spam with high accuracy.

Setup

1. Create and activate your virtual environment.

2. Install the dependencies:

   npm install

3. Install the required packages:

   pip install fastapi scikit-learn uvicorn imbalanced-learn nltk

Getting Started

To test this spam detection model, follow these steps:

1. Start the server:

   uvicorn spam_detection_api:app --reload --port 8001

2. Start the development server:

   npm run dev

3. Open http://localhost:5173 with your browser to see the result.

4. You are all set 🎉

Maintainers

This project is mantained by:

• Adel Mokadem
• Abdelnour Fellah
• Yacine Benyamina
• Abderrahmene Benounene

Contributions

Feel free to contribute to the project by opening issues, submitting pull requests, or providing feedback. Your contributions are highly welcome!