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https://github.com/abdullahashfaq-ds/sms-spam-detection
A machine learning application designed to classify SMS messages as spam or non-spam, offering real-time analysis to identify potentially harmful content.
https://github.com/abdullahashfaq-ds/sms-spam-detection
css3 docker flask html5 javascript matplotlib nltk numpy pandas python scikit-learn seaborn tailwindcss xgboost
Last synced: 8 days ago
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A machine learning application designed to classify SMS messages as spam or non-spam, offering real-time analysis to identify potentially harmful content.
- Host: GitHub
- URL: https://github.com/abdullahashfaq-ds/sms-spam-detection
- Owner: abdullahashfaq-ds
- License: mit
- Created: 2024-10-25T13:56:35.000Z (12 days ago)
- Default Branch: main
- Last Pushed: 2024-10-26T19:53:07.000Z (11 days ago)
- Last Synced: 2024-10-26T21:48:52.789Z (11 days ago)
- Topics: css3, docker, flask, html5, javascript, matplotlib, nltk, numpy, pandas, python, scikit-learn, seaborn, tailwindcss, xgboost
- Language: Jupyter Notebook
- Homepage:
- Size: 1.26 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# SMS Spam Detection
The SMS Spam Detection application is a machine learning tool designed to classify SMS messages as either spam or not spam. It utilizes a pre-trained model to analyze messages and identify potentially harmful content. Developed using the Flask web framework, the application features an interactive interface for real-time message classification.
**Dataset**: [SMS Spam Collection Dataset](https://www.kaggle.com/datasets/uciml/sms-spam-collection-dataset)
## Technologies Used
- **Backend**: Flask (Python)
- **Frontend**: HTML5, CSS3, TailwindCSS, JavaScript
- **Containerization**: Docker, Docker Compose
- **Machine Learning**: Scikit-learn, XGBoost, NLTK, Seaborn, Matplotlib, Pandas, NumPy
## Demo
## Installation
### Prerequisites
Ensure the following are installed on your local machine:
- Python 3.8+
- Docker and Docker Compose (optional for containerized deployment)
### Clone the Repository
```bash
git clone [email protected]:abdullahashfaq-ds/SMS-Spam-Detection.git
cd SMS-Spam-Detection
```
### Method 01: Virtual Environment Setup
```bash
python -m venv venv
# On Windows, use:
venv\Scripts\activate
# On Linux/MacOS, use:
source venv/bin/activate
# To set up the production environment:
pip install -r requirements.txt
# To set up the development environment:
pip install -r requirements.dev.txt
# To run the project:
python app.py
```
### Method 02: Docker Setup
For a containerized environment, build and run the container:
```bash
docker build -t spam-detection .
docker run -p 5000:5000 spam-detection
```
Access the application at `http://localhost:5000`
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.
## Contact
For inquiries or support, please open an issue on GitHub or contact [[email protected]](mailto:[email protected]).