In this course you will learn how to evaluate recommender systems. You will gain familiarity with several families of metrics, including ones to measure prediction accuracy, rank accuracy, decision-support, and other factors such as diversity, product coverage, and serendipity. You will learn how different metrics relate to different user goals and business goals. You will also learn how to rigorously conduct offline evaluations (i.e., how to prepare and sample data, and how to aggregate results). And you will learn about online (experimental) evaluation. At the completion of this course you will have the tools you need to compare different recommender system alternatives for a wide variety of uses.
Recommender Systems: Evaluation and Metrics
Recommender Systems: Evaluation and Metrics
This course is part of Recommender Systems Specialization
Instructors: Michael D. Ekstrand
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Gain insight into a topic and learn the fundamentals.
236 reviews
7 hours to complete
Flexible schedule
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5 assignments
Taught in English
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This course is part of the Recommender Systems Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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Showing 3 of 236
LL
Reviewed on Jul 18, 2017
wonderful!!! They teach a lot what I did not expect!
NS
Reviewed on Dec 13, 2019
Wonderful course provide realtime examples of the pros and cons of each approach and metric, very useful and enjoyable
CS
Reviewed on Jul 15, 2017
A lot of very in detail theories and metrics. I wish it could have more hands on experience.
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