Spam Email Detection using Naive Bayes
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Updated
May 9, 2021 - Python
Spam Email Detection using Naive Bayes
Email Spam Tool is a powerful application designed for testing and analyzing email systems by generating and sending bulk emails. This tool is meant for security professionals and developers to evaluate email filtering systems and anti-spam measures.
Email Spam Filter using SVM Classifier
This email spam checker uses two machine learning classifiers: kNN and Naive Bayes.
Python || Machine Learning
Email Spam detection using KNN and Decision Trees Models Trained using the Spambase database
Email Spam detection using Machine Learning
Using naive bayes classfier to predict spam
An end-to-end automated script that will check the latest email from your google mail account and give a brief report whether the email was spoofed or was supposedly impersonated!
Email Spam Detection using Machine Learning
All-in-One Email Extract & Scraper Pro is a powerful and comprehensive email extraction and scraping tool designed to help users extract email addresses from google,bing,yahoo etc search engines, and social media platforms,and google map
Create a `Naive Bayes` model for email spam detection
Some Machine Learning Experiments
Detected Spammed emails from an ‘SMS spam collection dataset’ with 98% accuracy. Used NLTK and Sklearn to preprocess the text data and classification.
A simple text classifier in Python that uses the Naive Bayes model to classify e-mails as spam or ham.
A repository containing a list of email addresses that will be identified as sources of spam or other types of fraud in the future.
A Python-based email spam detector using the Naive Bayes approach.
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