An Efficient Spam Email Filtering Approach Using Machine Learning

Abstract

Email is among the most extensively used
communication techniques. Fraud Emails or Spam
Emails has become a major concern as it is valueless to
the recipient. It is a wastage of network capacity and
filtering spam emails are time consuming and removing
all of these is a concerning issue. There are various
methods to categorize emails, such as Naïve Bayes,
SVM etc. This Paper proposes a system to predict spam
mails using machine learning in Google Colab a
Jupyter notebook environment.