An advanced email spam detection system leveraging machine learning techniques to accurately classify emails as spam or legitimate (ham) using Multinomial Naive Bayes classification.

The "Email Spam Detection" project focuses on classifying emails as spam or ham (non-spam) using a logistic regression model with TF-IDF feature extraction. The dataset "mail_data.csv" contains email …

Oct 28, 2023 · One of the primary methods for spam mail detection is email filtering. It involves categorize incoming emails into spam and non-spam. Machine learning algorithms can be trained to …

One of the primary methods for spam mail detection is email filtering. It involves categorize incoming emails into spam and non-spam. Machine learning algorithms can be trained to filter out spam mails …

Spam Email Detection is a critical feature for improving user experience and security by automatically identifying and filtering out unwanted emails. This project demonstrates how to build a spam …

Spam Email Detection with Machine Learning Introduction This project focuses on building an effective email spam detection system using Python and machine learning techniques. The primary objective …

Spam Mail Prediction using Python and Logistic Regression. This project classifies emails as spam or ham using a Kaggle dataset, TfidfVectorizer for feature extraction, and Logistic Regression for …

Spam-Detector-AI Spam-Detector-AI is a Python package for detecting and filtering spam messages using Machine Learning models. The package integrates with Django or any other project that uses …

Spam Detection Project for college students with PPT, Report, Code, Datasets and Research papers Abstract : Email Spam has become a major problem nowadays, with Rapid growth of internet users, …

This dataset contains 138,813 text entries, curated to support tasks such as text classification, spam detection, and multilingual analysis. Each entry includes a label (e.g., "ham" for non-spam or "spam") …