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The classifier helps users filter out unwanted emails by analyzing email content and metadata using various ML techniques.\n\n## ✨ Features\n\n- Email text preprocessing and cleaning\n- Feature extraction using TF-IDF vectorization\n- Machine learning classification model\n- High accuracy in distinguishing between spam and legitimate emails\n- Easy-to-use interface for email classification\n\n## 🛠️ Technologies Used\n\n- Python 3.x\n- scikit-learn\n- pandas\n- NLTK\n- NumPy\n- Seaborn\n- XGboost\n\n## 📋 Requirements\n\n```\npandas\u003e=1.2.0\nscikit-learn\u003e=0.24.0\nnltk\u003e=3.6.0\nnumpy\u003e=1.19.0\nseaborn\u003e=0.7.1\nxgboost\u003e=2.0.1\n```\n\n## 🚀 Installation\n\n1. Clone the repository\n\n```bash\ngit clone https://github.com/HanyMedhat10/Spam-Emails-Classify-ML.git\ncd spam-email-classifier-ML\n```\n\n2. Install required packages\n\n```bash\npip install -r requirements.txt\n```\n\n## 📊 Models comparison Accuracy\n\n\u003cimg src=\"./Model Comparison .png\"\u003e\n\n## 📊 The Best Model Performance\n\n- Accuracy: 98%\n- Precision: 99%\n- Recall: 98%\n- F1-Score: 98%\n\n## 🤝 Contributing\n\nContributions are welcome! Please feel free to submit a Pull Request.\n\n## 📝 License\n\nThis project is licensed under the MIT License - See the [LICENSE](LICENSE) file for details.\n\n## 👥 Contact\n\n- Hany Medhat\n- Email: \u003cHany.Medhat24@gmail.com\u003e\n- GitHub: [@HanyMedhat10](https://github.com/HanyMedhat10)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhanymedhat10%2Fspam-emails-classify-ml","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhanymedhat10%2Fspam-emails-classify-ml","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhanymedhat10%2Fspam-emails-classify-ml/lists"}