A Naive Bayes spam/ham classifier based on Bayes' Theorem. A bunch of emails is first used to train the classifier and then a previously unseen record is fed to predict the output.

AI-Mail-Classifier for Techfest IITB competition

Machine learning for filtering out spam in the ENRON spam dataset

Exploratory Analysis of Enron Dataset and Classification using multiple algorithms

A comprehensive comparision of kNN, Naive Bayes and Neural Network in Text Classification

Classification of emails received on a mass distribution group

a powerful tool designed to declutter and organize your inbox automatically using Cohere's classification API. Leveraging Node.js and the IMAP protocol, it fetches, parses, and classifies your emails into appropriate folders, facilitating a tidy and well-organized mailbox. Get started now to redefine your email management experience!

A ML classification example to train a Naive Bayes model to be able to predict who wrote a document/email, given the words used in it

SPAM Blocker is a program that pretends to be a mail classifier that detects SPAM and HAM (no spam mail).

A collection of Python scripts designed to streamline various tasks related to managing emails and PDF attachments. Easily extract clean email text, classify emails as automated or human-generated, process PDFs, and automatically fill PDF forms using saved user profile data.

Machine learning on spam

This repo has email classifiers based on Naive Bayes classifier, Bernouilli Naive Bayes Classifier and Logistic Regression Classifier.

Spam Email Detection using Naive Bayes

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.

Email Classification Tool

Developed a Naive Bayes classifier for classifying the E-mail is Spam or Ham message

This repository is made to support my application of MLH fellowship. This project had been done during my 2 years of work experience at Sailfin Technologies and is stored as a private repository before. The repository contains full process code from email cleaning, data modelling, database authentication (postgres for Salesforce), REST API build…

This Project is aimed at classifying emails into Spam or Non-Spam Category using KNN, Naive Bayes and Decision Trees. This project doesn't use any existing machine learning library for classification but just pure Python.

NaiveBayes classifier with an without stop words to classify Ham and Spam emails

A Naive Bayes algorithm to classify spam emails