The Spam Mail Classification project is a web-based application that uses machine learning to classify emails as spam or ham. It features a Flask backend, a frontend created with HTML, CSS, and JavaScript, and a MySQL database for storing user data and email classifications.
Used machine learning models to predict spam mails, loan, diabetes etc... also done web scraping, sentiment analysis, EDA. Have fun.
This project detect the spam mail and this prediction model accuracy_socre is 96% percentage . This project build by @GovindHede
Quick Spam Filter is a small, fast spam filter that works by learning to recognise the words that are more likely to appear in spam than non-spam. It is intended to be used in a procmail recipe to mark email as being possible spam.
A web app featuring five classification projects: Spam Mail Prediction, Titanic Survival Prediction, Wine Quality Prediction, Loan Status Prediction, and Credit Card Fraud Detection, all built with Streamlit.
Forwarded message or mail are fraud or not has been detected by our model using NLP.
Developed a Django-based email spam detection app with a unique hacker-themed interface, leveraging machine learning models to classify emails as spam or ham.
Spam mail detection using Logistic Regression Machine Learning model
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