spam-detection-machine-learning

End-to-end Email Spam Detection system using Machine Learning and NLP, featuring TF-IDF, Logistic Regression, threshold optimization, and a FastAPI-based real-time inference API.

🔥 Classify your email SPAM or HAM easily with the Machine Learning Algorithm, FAST API and User-Friendly UI.

React Application for detecting spam messages/emails

✨ spam detection using Bayesian Learning and Ensemble Learning. This repository implements Bayesian Learning from scratch

🛡️SMSGuard – An advanced Machine Learning–powered SMS Spam Detection system using TF-IDF and models like Naive Bayes, Logistic Regression, and SVM. Includes confusion matrix visualization, real-message testing, and custom SMS predictions. Perfect for cybersecurity, telecom filtering, and ML learning.

NLP email classification with governed data ingestion, leakage-resistant evaluation, Gmail/.eml inference, and reproducible ML pipelines.

Machine learning spam detection for french text

Комплексное решение для борьбы со спамом: сбор и анализ данных, обучение моделей, Telegram-бот и веб-панель для мониторинга.

The first AI system developed by QMA Labs — an intelligent security analyzer designed to bridge human awareness and machine intelligence. Using Machine Learning, NLP, and threat intelligence, it detects phishing, spam, and social engineering threats in the evolving digital world.

SMS Spam detection using techniques of natural language processing

Machine Learning Internship Tasks at CODSOFT - Movie Genre Classification, Credit Card Fraud Detection, Customer Churn Prediction & SMS Spam Detection

Spam and not-spam email classifier using Machine Learning, NLP, Python, Scikit-learn, and Jupyter Notebook for accurate detection.

End-to-end Email Spam Detection system using Machine Learning and NLP, featuring TF-IDF, Logistic Regression, threshold optimization, and a FastAPI-based real-time inference API.

This project implements an intelligent spam filter that combines the statistical learning of a Neural component (Logistic Regression) with the linguistic reasoning of Fuzzy Logic.

Explore and contribute to the Indian Telecom SMS Spam Collection.

Implement and Evaluate Naive Bayes for text classification

This project is a simple spam message classifier built using Python's Scikit-learn library. It uses a Multinomial Naive Bayes model combined with a Count Vectorizer to classify text messages as either Spam or Ham (Not Spam).

Live AI-powered SMS spam detection web app built with React, Django, NLP, and Scikit-learn.