The Email Spam Classifier is a machine learning application designed to predict whether an email is spam or not. This project uses scikit-learn for model training, Flask for creating a web interface, and Pickle for model serialization. It provides a simple yet effective solution for filtering spam emails with ease.
- Preprocessing of email text data.
- Machine learning model to classify emails as spam or not.
- Flask-based web interface for user interaction.
- Pickle-based model loading and prediction.
- Python: Programming language.
- Scikit-learn: For machine learning model training.
- Flask: For building the web application.
- Pickle: For saving and loading the trained model.
- Text Preprocessing Techniques: Cleaning, stemming, and feature extraction.
- Clone this repository:
git clone <repository_link> cd email-spam-classifier
- Install dependencies:
pip install -r requirements.txt
- Run the Flask application:
python app.py
- Open your browser and navigate to:
http://127.0.0.1:5000/
- Input: Users input email content into the web interface.
- Prediction: The application processes the input and predicts whether the email is spam or not.
- Output: The classification result is displayed on the web interface.
- Integration with email servers for automated classification.
- Improved text preprocessing techniques for higher accuracy.
- Deployment using Docker or cloud services for scalability.
Contributions are welcome! If you’d like to make improvements or report issues, please submit a pull request or open an issue in the repository.
This project is licensed under the MIT License. See LICENSE for details.
For queries or feedback, reach out to:
Let me know if you'd like to tweak anything or need further help! 😊