A Deep Graph-based Toolbox for Fraud Detection

Spam Filter AI is a project in Python that uses machine learning to detect spam emails. It uses Natural Language Processing (NLP) and Naive Bayes classification. The program reads email content, converts it into useful data with TF-IDF vectorization, and then decides if the email is spam or not, keeping your inbox clean and organized.

UltraClean is a fast and efficient Python library for cleaning and preprocessing text data for AI/ML tasks and data processing.

Deep Learning based Image Spam Detection

University Project - Spam Detection using ML-Algorithms in Python

This is a Spam-detector Web App created by using Flask.

A spam detection model built to handle imbalanced data using small pipelines. This project walks through text preprocessing, model tuning, and performance evaluation with ROC-AUC curves and classification reports, focusing on practical steps like using XGBoost and TFIDF for spam classification.

8:22 AMSMS Spam Detection using NLP & Machine Learning — classifying messages as Spam or Ham with 95.78% accuracy.

Spam Detection Program This is a simple Spam Detection System built using Python and Machine Learning.

Rakshak is a hackathon project that integrates a chatbot to answer questions related to spam or ham classifications. It features a highly accurate pre-trained ML module that classifies spam and ham messages, texts, emails, and phone numbers. This ensures effective and reliable identification of spam across various communication channels.

Email Spam Classifier using Naive Bayes ML algorithm achieving 98% accuracy. Features interactive testing, confidence scores, auto-generated visualizations (confusion matrix, performance charts), and model persistence. Built with Python, scikit-learn, and pandas. Perfect for learning ML text classification!

Its a custom trained spamDetector using logistic regression with bow vectorizer

NLP spam classifier using TF-IDF and Linear SVM achieving 98.47% accuracy, with a Flask web app for real-time spam detection.

contains project related to python

This project aims to design and develop a robust spam detection system that can accurately classify incoming messages or emails as spam or legitimate. Spam Detection Project Project Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials

Machine Learning algorithm used to distinguish between spam and ham texts.

SMS Spam Detection App is a machine learning project built with Python, using NLP techniques and libraries like scikit-learn, NLTK, and Pandas. It classifies SMS messages as spam or not spam based on text analysis and supervised learning models . The app includes text preprocessing steps and TF-IDF vectorization for effective spam detection.