Spam Email Classifier

A machine learning model that classifies emails as spam or legitimate using natural language processing techniques.

🎯 Project Overview

This project implements a machine learning model to automatically detect and classify spam emails. The classifier helps users filter out unwanted emails by analyzing email content and metadata using various ML techniques.

✨ Features

• Email text preprocessing and cleaning
• Feature extraction using TF-IDF vectorization
• Machine learning classification model
• High accuracy in distinguishing between spam and legitimate emails
• Easy-to-use interface for email classification

🛠️ Technologies Used

• Python 3.x
• scikit-learn
• pandas
• NLTK
• NumPy
• Seaborn
• XGboost

📋 Requirements

pandas>=1.2.0
scikit-learn>=0.24.0
nltk>=3.6.0
numpy>=1.19.0
seaborn>=0.7.1
xgboost>=2.0.1

🚀 Installation

1. Clone the repository

git clone https://github.com/HanyMedhat10/Spam-Emails-Classify-ML.git
cd spam-email-classifier-ML

2. Install required packages

pip install -r requirements.txt

📊 Models comparison Accuracy

📊 The Best Model Performance

• Accuracy: 98%
• Precision: 99%
• Recall: 98%
• F1-Score: 98%

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📝 License

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

👥 Contact

• Hany Medhat
• Email: Hany.Medhat24@gmail.com
• GitHub: @HanyMedhat10