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.

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.

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

Deep Learning based Image Spam Detection

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.

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

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

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