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This project leverages the Enron email dataset to build a spam detection model using classical machine learning techniques. The model processes and classifies emails based on their subject lines and message bodies, with a final accuracy of 90–91% using Logistic Regression and Multinomial Naive Bayes classifiers.
maheshvarade/Enron-Spam-Detection-using-NLP-ML
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This project leverages the Enron email dataset to build a spam detection model using classical machine learning techniques. The model processes and classifies emails based on their subject lines and message bodies, with a final accuracy of 90–91% using Logistic Regression and Multinomial Naive Bayes classifiers.
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