📩 Spam Classifier Streamlit App

A simple Streamlit web app that predicts whether a message is Spam or Ham (not spam) using a machine learning model trained on text data.

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🚀 Features

• Instant Classification: Enter a message and classify it instantly as Spam or Ham.
• Machine Learning Powered: Uses a saved TfidfVectorizer and Logistic Regression model.
• User-Friendly: Clean, simple interface built with Streamlit.

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🛠️ Installation

1. Clone the repository:

   git clone https://github.com/yourusername/spam-classifier-streamlit.git
   cd spam-classifier-streamlit
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Ensure you have the following files in the root directory:

   • app.py (the Streamlit app)
   • vectorizer.pkl (saved TfidfVectorizer)
   • model.pkl (saved Logistic Regression model)

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🚦 Usage

Run the app locally:

streamlit run app.py

• Enter a message in the input box.
• Click Predict to see if it’s Spam or Ham.

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📝 Example

Message: "Congratulations! You've won a free ticket." Prediction: Spam 🎉

Message: "Hey, are we meeting for coffee today?" Prediction: Ham ☕

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📦 Requirements

• Python 3.7+
• Streamlit
• scikit-learn
• joblib or pickle

All dependencies are listed in requirements.txt.

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🧠 Model Info

• Vectorizer: TfidfVectorizer (pre-trained and saved as vectorizer.pkl)
• Classifier: Logistic Regression (pre-trained and saved as model.pkl)

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🤝 Contributing

Pull requests are welcome! For major changes, please open an issue first to discuss what you would like to change.

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📄 License

MIT

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🙋‍♂️ Acknowledgements

• Streamlit
• scikit-learn
• SMS Spam Collection Dataset

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Happy classifying! 🚀