A Comparative Analysis of Deep Learning Approaches for Email Spam Detection

In this digitization world, Email is used everywhere in this world, from the business to the education. Emails are divided into two subparts that is SPAM and HAM. Email-spam, also known as junk emails or unwanted mails, these are the types of email which is used by hackers or attackers for the hacking of your system and also some people used this to do prank with others. The large number of unwanted mails which is called spam has become a very critical need for the development of more dependable and an accurate filter algorithm. The ratio of SPAM email is increasing very rapidly. filtering and blocking of the SPAM emails are the two main factor by which we can stop this SPAM mails. There are many filtering algorithms, which have been made by the help of different ML models known as Naïve Byes, DT known as decision trees, also neural networks etc. This research includes the ML algorithm which is used for filter the fake emails.