Developing A Spam Detection Application — Machine Learning For Beginners

In this article we will dive into the development of a simple but effective Spam Detection application using the Python Programming language and Bayes Theorem. But first lets take a look at what spam detection is and how such is already a part of our everyday life.

As a user of the internet you have most certainly been in contact with spam detection applications either with or without your knowledge as these operates in the background of almost every mail provider, forums or social media platforms. In it’s simplicity the job of such applications is to ensure that certain content will never be displayed to the end users. This however is often a challenging task as there is no such thing as a 100% accuracy spam detection rate in real life scenarios. This is true due to the way that spam is classified differently across each use case. e.g. Outlook might categorize mails with multiple occurrences of the word “FREE” as possible spam, whereas a forum dedicated to share coupons and good offers between it’s users will see the word “FREE” occur a lot in legitimate posts. The main goal of developing a Spam Detection Application is therefor to train it towards the context in which it’s to be used.

For more stories by Vinsloev Academy, sign up as a member and support our work…