Detects and blocks spam and fraud in Django apps without CAPTCHAs, ensuring seamless user experience.

A repository containing a list of email addresses identified as sources of spam or other types of fraud.

This project aims to develop a machine learning-based system for detecting spam emails. Email Spam Detection Project With Code, Documents, PPT, Report and Video

Email-Sms-Spam-Classifier

Spam mail, or junk mail, is a type of email that is sent to a massive number of users at one time, frequently containing cryptic messages, scams, or most dangerously, phishing content.

Laptop with Browser Icon We’ve all been the recipient of spam emails before. Spam mail, or junk mail, is a type of email that is sent to a massive number of users at one time, frequently containing cryptic messages, scams, or most dangerously, phishing content.

Built a real-world email spam classifier using Support Vector Machine(SVM), achieving 98% accuracy through robust text preprocessing, TF-IDF feature extraction, and EDA. Deployed the model with Flask, enabling real-time predictions and visualization of words influencing classification.

A machine learning-based email spam detection system integrated with a Flask web app. The project uses a trained logistic regression model to classify emails as spam or not spam, utilizing TfidfVectorizer for feature extraction and providing real-time predictions through a simple API.