Recommender Systems: Evaluation and Metrics

Recommender Systems: Evaluation and Metrics

Recommender Systems: Evaluation and Metrics This course is part of Recommender Systems Specialization Taught in English 22 languages available Some content may not be translated Instructors: Michael D. Ekstrand +1 more Close Instructors Instructor ratings We asked all learners to give feedback on our instructors based on the quality of their teaching style. Close 4.9

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Recommender Systems: Evaluation and Metrics

Recommender systems have become a ubiquitous part of our daily lives, helping us discover new products, services, and content tailored to our preferences. These systems use algorithms to analyze user data and provide personalized recommendations, making them essential tools for businesses looking to improve customer satisfaction and engagement. However, evaluating the performance of recommender systems is a complex and challenging task that requires careful consideration of various metrics and evaluation techniques.

One of the primary challenges in evaluating recommender systems is determining how to measure their effectiveness accurately. While traditional metrics like accuracy and precision are commonly used, they may not always provide a complete picture of a system’s performance. For example, accuracy measures the percentage of correct recommendations made by the system, but it does not take into account the

Recommender Systems: Evaluation and Metrics

This course is part of Recommender Systems Specialization

Taught in English

Some content may not be translated

Michael D. Ekstrand
Joseph A Konstan

Instructors: Michael D. Ekstrand

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7 hours (approximately)
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