sms_spam_classifier

This project is an SMS Spam Classifier built using the Naive Bayes Algorithm and deployed with Streamlit. The application classifies SMS messages as either spam or not spam, providing a simple and efficient solution for spam detection.

Features

• Classifies SMS messages as spam or non-spam.
• User-friendly web interface powered by Streamlit.
• Interactive input for message classification.
• Accurate and fast classification using Naive Bayes.

Installation

1. Clone the repository:

   git clone https://github.com/BhoomiAgrawal12/sms_spam_classifier.git  
   cd sms-spam-classifier  

2. Create and activate a virtual environment (optional but recommended):

   python3 -m venv env  
   source env/bin/activate  # On Windows: env\Scripts\activate  

3. Install the required dependencies:

   pip install -r requirements.txt  

4. Run the application:

   streamlit run app.py  

Usage

1. Navigate to the Streamlit app in your browser (default: http://localhost:8501).
2. Enter an SMS message in the text box.
3. Click the "Classify" button to see the prediction (Spam/Not Spam).

Project Structure

• app.py: Main file containing the Streamlit application.
• spam_classifier.py: Contains the Naive Bayes implementation and preprocessing steps.
• requirements.txt: List of dependencies for the project.
• README.md: Documentation for the project.

Technology Stack

• Language: Python
• Libraries: Streamlit, Scikit-learn, Pandas, Numpy

Contribution

We welcome contributions! Please see the CONTRIBUTING.md file for guidelines.

License

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

Contact

For questions or feedback, please reach out through my mail:
bhoomiagrawal1212.com