Abstract
In today's world, email spam has become a serious concern, since the number of internet users has grown rapidly. Illegal and unethical practices, such as phishing and fraud, are taking advantage of the diverse classes of users that use different web services. Users that send unsolicited emails with the intention of disrupting or attracting legitimate customers are known as "spammers" by infecting the user system by sending malicious links in a spam email. Spammers prey on those who are unaware of their deceptions by posing as real people in their unsolicited emails and setting up bogus social media profiles and email accounts. These fraudulent spam emails must be identified. The work is an attempt to analyze different machine learning approaches to serve the purpose. This article uses Deep Learning methods for the identification of spam emails with high precision and accuracy.
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