📧 SMS and Email Spam Classifier Welcome to the SMS and Email Spam Classifier! This project leverages machine learning to distinguish between spam and non-spam messages/emails, ensuring your inbox stays clean and organized.

🚀 Overview This project features a machine learning model trained to detect spam in both SMS and email messages. The accompanying interactive web application allows users to simply paste their message/email into the input box and click the "Predict" button to instantly see if it's spam or not.

📸 Interactive Web Page

✨ Features Accurate Spam Detection: Utilizes a well-trained machine learning model for high accuracy.

Dual Functionality: Works seamlessly with both SMS and email messages.

User-Friendly Interface: Easy to use web application for quick predictions.

Real-Time Processing: Get instant results with just a single click.

📜 How to Use Clone the Repository:

sh

Copy git clone https: https://github.com/Sanketx125/SMS-spam-Classifier-.git cd spam-classifier Install Dependencies:

sh

Copy pip install -r requirements.txt Run the Application:

sh

Copy streamlit run app.py Use the Web Interface:

Paste the received message/email into the input box.

Click the "Predict" button.

See if the message is spam or not.

🧠 Model Details Model Type: Machine Learning Classifier

Algorithm: Naive Bayes (Multinomial Naive Bayes)

Training Data: Dataset of SMS and email messages labeled as spam or not spam.

📂 Project Structure

Copy ├── app.py # Main application file ├── model.pkl # Trained machine learning model ├── vectorizer.pkl # TF-IDF Vectorizer ├── requirements.txt # List of dependencies ├── text_transformer.py # Text transformation functions ├── README.md # Project description and usage guide ├── spam-detection.ipynb # Machine Leanrning model ├── spam.csv # dataset

🤝 Contributing Contributions are welcome! If you find any issues or have suggestions for improvement, feel free to create a pull request or open an issue.