Built a real-world email spam classifier using Support Vector Machine(SVM), achieving 98% accuracy through robust text preprocessing, TF-IDF feature extraction, and EDA. Deployed the model with Flask, enabling real-time predictions and visualization of words influencing classification.
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Updated
Nov 2, 2025 - CSS