spam-filtering-system

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ShehanSanjula / Spam-Email-Filtering-System-Public

End-to-end implementation of Spam Detection in Email using Machine Learning, Python, Flask, Gunicorn, Scikit-Learn, and Logistic Regression on the Heroku cloud application platform.

python heroku machine-learning flash numpy linear-regression scikit-learn jupyter-notebook gunicorn pandas dataset email-validation spam-filtering spam-detection precision content-filtering accuracy-metrics spam-filtering-system

Updated Jan 15, 2023
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bhargav-joshi / Spam-Emails-Detection

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Spam Emails Detection Using Machine Learning with 99% Accuracy

machine-learning email-filter spam-filtering-system spam-emails-detection

Updated Mar 15, 2021
Jupyter Notebook

Gaurav241 / Email-SMS-Spam-Classifier

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The project leverages Naive Bayes Classifiers, a family of algorithms based on Bayes’ Theorem, which presumes independence between predictive features. This theorem is crucial for calculating the likelihood of a message being spam based on various characteristics of the data.