MrMDrX / Email-Spam-Detector

This repository contains a web application for detecting email spam using machine learning. The project includes a Jupyter Notebook (email-spam-detector.ipynb) for data analysis and model building, as well as a Flask web app (main.py) for deploying the trained model.

Email Spam Detector

Welcome to the Email Spam Detector project repository! This project focuses on building a spam detection system using natural language processing techniques. The detector analyzes text data to classify emails as either spam or legitimate (ham).

Project Structure

• data: Contains the dataset used for training and testing (spam.csv).
• email-spam-detector.ipynb: Jupyter Notebook containing the main code and documentation.
• main.py: Python script for running the spam detection model.
• models: Directory to store trained model files (model.pkl and vectorizer.pkl).
• README.md: You are here! Provides an overview of the project.
• requirements.txt: Lists project dependencies for easy environment setup.
• screenshots: Contains screenshots for illustration (ham.png and spam.png).
• static: Static files for the web application.
  • img: Images used in the web application (logo-64x64.png).
• templates: HTML templates for the web application.
  • index.html: Main page template.

Quick Start

1. Clone the repository:

   git clone https://github.com/MrMDrX/Email-Spam-Detector.git

2. Navigate to the Project Directory:

   cd Email-Spam-Detector

3. Create and Activate a Virtual Environment (Optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows, use 'venv\Scripts\activate'

4. Install dependencies:

   pip install -r requirements.txt

5. Run the spam detector:

   python main.py

Web Application

The project includes a simple web application for testing the spam detector. The web application is built using Flask and integrates HTMX for dynamic content updates. Access the application by running main.py and visiting http://localhost:5000 in your web browser.

Screenshots

• Ham (Legitimate Email)

• Spam

Notes

• The model and vectorizer files (model.pkl and vectorizer.pkl) in the models directory are essential for the spam detection functionality.

Contributing

If you'd like to contribute to this project, feel free to fork the repository and submit a pull request. You can also open issues for bug reports or feature requests.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Happy coding!