USING MACHINE LEARNING AND NLP TECHNIQUES FOR EFFICIENT SPAM EMAIL DETECTION

Abstract

Email spam has become a prevalent issue in recent times, with the growing number of internet users, spam emails are also on the rise. Many individuals use them for illegal and unethical activities such as phishing and fraud. Spammers send dangerous links through spam emails, which can harm our systems and gain access to personal information. It has become easier for criminals to create fake profiles and email accounts. They often impersonate real individuals in their spam emails, making them difficult to identify. This project aims to identify and detect fraudulent spam messages. The paper will explore the use of machine learning techniques, algorithms, and apply them to data sets. The goal is to select the best methods for maximum precision and accuracy in email spam detection.