A machine learning project for detecting spam messages using Python. This notebook demonstrates end-to-end text classification with preprocessing, feature extraction using TF-IDF, and model training using scikit-learn. Ideal for learning spam detection with real-world SMS data (from UCI).
Features:
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Dataset loading and inspection
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Text preprocessing and label encoding
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TF-IDF vectorization
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Model training and evaluation (Logistic Regression / Naive Bayes)
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Performance metrics (accuracy, precision, recall, F1)
Tech Stack:
- Python, Pandas, Scikit-learn, Seaborn, Matplotlib