email-classifier

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.

Machine learning for filtering out spam in the ENRON spam dataset

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

Automatically classify and organize Gmail emails using LLM-powered categorization. Stateless, taxonomy-driven, runs incrementally.

Gmail AI helper that classifies and prioritizes emails using Python, Gmail API, Redis and LLMs.

AI-powered Email Classifier with Reply Generator | FastAPI + React + scikit-learn | ML-based classification (high_priority/normal/spam) + auto-reply suggestions | Docker + Nginx production-ready | Full-stack ML project

Machine Learning powered Email Spam Detection Platform built with Streamlit, Scikit-Learn, TF-IDF and Naive Bayes.

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.

Intelligent Email Classification & Auto-Response System A modern web application that automatically classifies emails as productive/unproductive, detects intent (meeting, approval, budget, notification), and suggests contextual responses. Built with FastAPI, Alpine.js, and deployed on AWS Lambda for serverless scalability.

A realistic RL environment for training LLM agents on enterprise email triage—featuring multi-step decision making, ambiguity handling, tool usage, and deterministic evaluation.

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

This is a Spam Email Classifier built using Python and Streamlit. It uses a pre-trained model to predict whether an email is Spam or Not Spam. The app also provides the probability scores for both categories, enhancing transparency and reliability of the prediction.

Open-source phishing classifier achieving high accuracy with machine learning. Demonstrates NLP, RandomForest algorithms, and model optimization. Includes training data, GUI, and performance metrics.

AI-powered Email Spam Detection system using Machine Learning and NLP techniques.

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

Spam Email Detection using Naive Bayes

AI-powered Spam Email Classifier using TF-IDF and Multinomial Naive Bayes to classify messages as Spam or Ham.

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

Machine Learning based Gmail spam detection system using FastAPI, React, TF-IDF, Multinomial Naive Bayes, and Gmail API integration.

A Naive Bayes algorithm to classify spam emails