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Spam-Detection-using-Multinomial-Naive-Bayes

Detecting spam alerts in emails and messages is one of the main applications that every big tech company tries to improve for its customers. Apple’s official messaging app and Google’s Gmail are great examples of such applications where spam detection works well to protect users from spam alerts. So, if you are looking to build a spam detection system, this repository is for you. In this repository, I will walk you through the task of Spam Detection with Machine Learning using Python.

Spam Detection

Whenever you submit details about your email or contact number on any platform, it has become easy for those platforms to market their products by advertising them by sending emails or by sending messages directly to your contact number. This results in lots of spam alerts and notifications in your inbox. This is where the task of spam detection comes in.Spam detection means detecting spam messages or emails by understanding text content so that you can only receive notifications about messages or emails that are very important to you. If spam messages are found, they are automatically transferred to a spam folder and you are never notified of such alerts. This helps to improve the user experience, as many spam alerts can bother many users.

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