Here we present an inclusive review of recent and successful content-based e-mail spam filtering techniques. Our
focus is primarily on machine learning-based spam filters and variants that are inspired by them. We report on related ideas,
techniques, major efforts and cutting-edge art in the field. Preliminary interpretation of prior work shows the basics of e-mail
spam filtering and feature engineering. In this we conclude by studying techniques, methods, evaluation criteria, and explore
promising apprehensions of the latest developments and suggest future lines of investigation
