A machine learning project that classifies messages as 🚨 Spam or ✅ HAM, featuring a clean, fast, and user-friendly interface.
- Trains a Naive Bayes Classifier using an SMS spam dataset
- Uses CountVectorizer for text feature extraction
- Use 5300 sample data from Kaggle
- 98% accuracy on test data
- Real-time prediction through a clean UI
- Lightweight model — predictions under 1 second
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Could be extended into a browser extension, WhatsApp bot, or email scanner for automatic spam detection.