Introduction to Recommender Systems: Non-Personalized and Content-Based
University of Minnesota
In modern society, the recommender systems are everywhere and people even won’t survive without them. There are sorts of companies mining data of your behavior and creating profiles for you. They know you better than you do, and they affect almost all kinds of decisions you make everyday. Sometimes it is hard to tell whether “you enjoy being recommended” or the recommenders are dominating you. ๐
Despite the horrific scene that you are actually a slave, it is quite interesting to understand how recommender systems work. This course is the first one in the specialization, it focuses on the basics and the most fundamental types of recommenders: non-personalized and content-based.
The course is not difficult to understand for most of the people. It helps you get familiar with concepts and enables you to realize what is relevant under the hood. If you know how to use spreadsheet and have some knowledge of statistics, that is enough to complete the course. In case you know how to program in Java, following the Honor track will let you learn more and be more fruitful.
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