Implementing your own spam filter by Cambridge Coding Academy

This post teaches you how to implement your own spam filter in under 100 lines of Python code. While doing this hands-on exercise, you'll work with natural language data, learn how to detect the words spammers use automatically, and learn how to use a Naive Bayes classifier for binary classification. The task is to distinguish between two types of emails, "spam" and "non-spam" often called "ham". The machine learning classifier will detect that an email is spam if it is characterised by certain features. The textual content of the email – words like "Viagra" or "lottery" or phrases like "You've won a 100,000,000 dollars!