An Efficient Spam Email Filtering Approach Using Machine Learning

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.