Contextual bandits are a type of machine learning problem that sits between multi-armed bandits and reinforcement learning. They are used in online decision-making scenarios, like recommending products. Why are they cool?

[EDIT] Take a look at this data science glossary instead: https://www.datacamp.com/blog/data-science-glossary

This is a test post.