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You can download it from [](python.org)\n\n## Requirements\nEnsure you have the following dependencies installed. You can install them using `pip install -r requirements.txt`.\n\n- gunicorn==22.0.0\n- python-dateutil==2.8.2\n- gradio==4.32.1\n- gradio_client==0.17.0\n- requests==2.31.0\n- beautifulsoup4==4.12.3\n- googlesearch_python==1.2.4\n- urlextract==1.9.0\n- numpy==1.26.3\n- pandas==2.2.0\n- scikit-learn==1.5.0\n- urllib3==2.1.0\n- python-whois==0.9.4\n- xgboost==2.0.3\n- lxml==5.2.2\n\n## Setup and Installation\n\n1. Clone the repository:\n\n   ```bash\n   git clone https://github.com/your-username/email-spam-phishing-detection.git\n   cd email-spam-phishing-detection\n\n2. Install dependencies:\n   ```bash\n   pip install -r requirements.txt```\n   \n## Usage\n1. **Data Preparation:**\n   - Ensure the datasets `spam.csv` and `urldata.csv` are available in the `data/` directory.\n\n2. **Model Training:**\n   - If necessary, modify and run the `notebook.ipynb` Jupyter notebook to train or fine-tune the machine learning models.\n   - Trained models will be saved in the `models/` directory.\n\n3. **Run the Application:**\n   - Execute `app.py` to start the application.\n   - Access the application at [Hugging Face Space](https://huggingface.co/spaces/akshatsanghvi/spam-email-detection)\n\n## Acknowledgements\n\n- The email spam classification model is trained using the `spam.csv` dataset, sourced from [Dataset: Spam/ham mail](https://www.kaggle.com/datasets/mfaisalqureshi/spam-email?resource=download)).\n- The URL phishing detection model is trained using the `urldata.csv` dataset, sourced from [Phishing Websites Dataset](https://www.kaggle.com/datasets).\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fiiakshat%2Fspam-mail-detection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fiiakshat%2Fspam-mail-detection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fiiakshat%2Fspam-mail-detection/lists"}