A key to one of most sophisticated and effective approaches in machine learning and recommendation is contained in the observation: “I want a pony.” As it turns out, building a simple but powerful recommender is much easier than most people think, and wanting a pony is part of the key. Machine learning, especially at the scale of huge datasets, can be a daunting task. There is a dizzying array of algorithms from which to choose, and just making the choice between them presupposes that you have sufficiently advanced mathematical background to understand the alternatives and make a rational choice. The options are also changing, evolving constantly as a result of the work of some very bright, very dedicated researchers who are continually refining existing algorithms and coming up with new ones. Practical Machine Learning: Innovations in Recommendation