An AI-powered Spam Classifier built using Machine Learning and NLP techniques. It processes and transforms text using TF-IDF and predicts whether a message is Spam 🚨 or Not Spam ✔ using a trained model. The project is deployed end-to-end on Render with a Streamlit interface for real-time interaction.
- Classifies SMS/Email as Spam or Not Spam
- Text preprocessing (lowercasing, stopword removal, stemming)
- TF-IDF vectorization
- Machine Learning model for prediction
- Simple and interactive Streamlit web app
- Fast and lightweight (optimized for deployment)
- Deployed on Render for live access 🌐
- Python 🐍
- Streamlit
- Scikit-learn
- NLTK
- NumPy & Pandas
- Render
project/ │── app.py │── model.pkl │── vectorizer.pkl │── README.md │── requirements.txt │── Spam-classifier.ipynb
git clone https://github.com/your-username/spam-classifier.git
cd spam-classifier
2. Create virtual environment (optional but recommended)
python -m venv venv
source venv/bin/activate # for Linux/Mac
venv\Scripts\activate # for Windows
3. Install dependencies
pip install -r requirements.txt
4. Run the app
streamlit run app.py
🌐 Deployment
This project is deployed using Streamlit on Render.
To deploy:
Push code to GitHub
Connect repo to Render
Set start command:
streamlit run app.py
📌 Future Improvements
Improve model accuracy
Add deep learning (LSTM/BERT)
Enhance UI design
Add multi-language support