📧 Spam Email Classifier

📌 Overview

The Spam Email Classifier is a Machine Learning project that classifies emails as Spam or Ham (Not Spam).
It uses Natural Language Processing (NLP) and Machine Learning algorithms to achieve high accuracy in detecting spam emails.

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🚀 Features

• Preprocessing of raw email text (tokenization, stopword removal, TF-IDF vectorization).
• Trained ML model for binary classification (Spam / Ham).
• Interactive Hugging Face demo for real-time testing.
• Easy to extend with deep learning models in the future.

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🗂 Dataset

The model was trained on the popular Spam Email Dataset containing thousands of spam and ham messages.
It ensures balanced training for reliable predictions.

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🛠️ Technologies Used

• Python 🐍
• Scikit-learn
• Pandas & NumPy
• NLTK (for text preprocessing)
• Hugging Face Spaces + Gradio (for live demo)

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📸 Screenshots

(Add your screenshots here: training plots, confusion matrix, Hugging Face demo UI)

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🔴 Live Demo

👉 Try the model on Hugging Face: Spam Email Classifier Demo

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📈 Results

• Achieved high accuracy on the test dataset.
• Correctly identifies spam vs ham messages.
• Reliable predictions on unseen emails.

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🔮 Future Improvements

• Add deep learning models (LSTM / Transformer-based).
• Support for multiple languages.
• Deploy as a browser extension for real-time email classification.

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👨‍💻 Author

Muhammad Rayan Shahid
AI & ML Enthusiast

🌐 GitHub
💼 LinkedIn
📊 Kaggle
🤗 Hugging Face
🎥 YouTube - ByteBrilliance AI

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