Introduction to Machine Learning with Python's Scikit-learn Codementor

In this post, we'll be doing a step-by-step walkthrough of a basic machine learning project, geared toward people with some knowledge of programming (preferably Python), but who don't have much experience with machine learning. By the end of this post, you'll understand what machine learning is, how it can help you, and be able to build your own machine learning classifiers for any dataset you want. We'll teach a computer how to distinguish between "clickbait" headlines and "normal" headlines, where the former are those irritating "You won't believe what X does to Y" type headlines that deliberately withhold information to try to make people click on the article. Traditionally, to write such a classifier, we would manually inspect hundreds of clickbait headlines and try to identify patterns to differentiate them from "good" headlines. We would then write a script with a lot of hand-crafted rules that tries to discriminate between clickbait headlines and good ones. This is a time consuming process that requires an expert to create the rules, and requires a lot of code maintenance, because we would probably need to continuously update and modify the rules.