This is a tutorial about real-world use of interactive and online learning. We focus on systems for practical applications ranging from recommendation tasks and ad-display, to clinical trials and adaptive decision making in computer systems. There is quite a bit of foundational theory and algorithms from the field of machine learning yet practical use is fraught with several challenges. Success in interactive learning requires a complete learning system which handles exploration, data-flow, logging and real-time updating supporting the core algorithm.

Each potential application also comes with multiple design choices and often do not fit the setting in theory as-is. We cover both foundational principles which have proved practically essential as well as recipes for success from practical experience. After the tutorial, participants should have both a firm understanding of the foundations and the practical ability to deploy and start using such a system in an hour.