Spam Mail Detection using Machine Learning

Abstract

The aim is to create a spam filter that is efficient enough to enhance email security and productivity. Then we will evaluate some ML algorithms like Naive Bayes, Support Vector Machines (SVM) or Random Forests to find out which is going to be the best model to classify spam. Spam emails have become the bane of the internet world, but they have also turned to be a huge problem in the world of criminal activities such as phishing scams and frauds; as spam emails became more common, they needed better anti spam filters. Nowadays, machine learning techniques are used to detect and filter spam emails successfully. This study reviews popular machine learning based spam filters and their strengths, weaknesses and future directions. It also talks about how Gmail and Yahoo use machine learning to filter spam.