This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summary statistics and product associations, basic stereotype-based or demographic recommendations, and content-based filtering recommendations.
This course is part of the Recommender Systems Specialization
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About this Course
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- Summary Statistics
- Term Frequency Inverse Document Frequency (TF-IDF)
- Microsoft Excel
- Recommender Systems
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Syllabus - What you will learn from this course
Preface
Introducing Recommender Systems
Non-Personalized and Stereotype-Based Recommenders
Content-Based Filtering -- Part I
Content-Based Filtering -- Part II
Course Wrap-up
Reviews
- 5 stars60.76%
- 4 stars29.50%
- 3 stars6.22%
- 2 stars1.75%
- 1 star1.75%
TOP REVIEWS FROM INTRODUCTION TO RECOMMENDER SYSTEMS: NON-PERSONALIZED AND CONTENT-BASED
Great, thorough introduction with tracks for both Java programmers and non-programmers.
Great course. I have already been able to apply what I have learned to me job. Looking forward to the next one.
Please update the specialization, it's 2022, and the course slides are from 2016.
More information on Programming Assignment would have been helpful . Overall a good course to begin the specialization
About the Recommender Systems Specialization

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