📱 SMS Spam Classifier

A simple Machine Learning project that classifies SMS messages as SPAM or NOT SPAM using Python, scikit-learn, and Streamlit.

This project demonstrates an end-to-end ML workflow: dataset handling, model training, evaluation, saving, and creating an interactive demo for recruiters or users.

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📂 Project Structure

spam-classifier/
├─ data/                     # Dataset: SMSSpamCollection
├─ models/                   # Trained model saved here
├─ train.py                  # Script to train the model
├─ app.py                    # Streamlit interactive demo
├─ requirements.txt          # Project dependencies
└─ README.md

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🛠 Tools & Libraries

• Python 3.x
• pandas – Data handling
• scikit-learn – Machine Learning (TF-IDF, Naive Bayes)
• joblib – Save/load model
• Streamlit – Interactive web demo

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💾 Dataset

• SMS Spam Collection Dataset
• Place the file SMSSpamCollection in the data/ folder before running the scripts.

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⚡ How to Run

1️⃣ Clone the repository

git clone https://github.com/EmranZZ/SPAM-Detection
cd spam-classifier

2️⃣ Create virtual environment & install dependencies

python -m venv venv
venv\Scripts\activate   # On Windows
source venv/bin/activate   # On Linux/Mac

pip install -r requirements.txt

3️⃣ Train the Model

python train.py

• Trains the Naive Bayes classifier
• Saves model in models/spam_classifier.joblib

4️⃣ Run the Interactive Demo

streamlit run app.py

• Opens a browser
• Enter any SMS message
• Get SPAM / NOT SPAM prediction with probability

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📊 Results

• Accuracy: ~95%
• Confusion matrix and classification report printed during training

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📸 Screenshot

Add a screenshot of your Streamlit demo here for recruiters

Example:

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💼 Author

MOHAMMAD EMRAN AHMED

• GitHub: github.com/EmranZZ
• Email: ahmed777emran@gmail.com