This project is a machine learning-based solution to classify SMS messages as either "Spam" or "Not Spam". It also includes a deployed webpage where users can input SMS messages to check their classification in real-time.
- SMS Classification: Uses a trained machine learning model to classify SMS messages.
- Webpage Deployment: A user-friendly webpage for testing SMS messages.
- Interactive Interface: Input SMS messages and get instant results.
data/: Contains datasets used for training and testing.model/: Includes the trained machine learning model.webapp/: Code for the deployed webpage.notebooks/: Jupyter notebooks for data exploration and model training.README.md: Project documentation.
- Clone the repository:
git clone https://github.com/IbrahimBagwan1/ML-Project-Sms-Scam-Classify.git- Navigate to the project directory:
cd ML-Project-Sms-Scam-Classify- Install the required dependencies:
pip install -r requirements.txt- Run the Web Application:
python app.py- Open your browser and navigate to
http://127.0.0.1:5000/. - Input an SMS message to classify it as "Spam" or "Not Spam".
The webpage is deployed using Flask. You can deploy it on platforms like Heroku or AWS for public access.
- Algorithm: (Selected): Naive Bayes, (Checked for): SVM, RandomForest, Adaboost, XGBBoost, etc.
- Accuracy: 0.97
- Precision: 1.00
Contributions are welcome! Please fork the repository and submit a pull request.
This project is licensed under the MIT License.
For any queries, feel free to reach out:
- Author: Ibrahim Bagwan
- GitHub: IbrahimBagwan1