What Is Data Analysis? (With Examples)
October 2, 2024
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This course is part of Recommender Systems Specialization
Instructors: Joseph A Konstan
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In this course, you will learn the fundamental techniques for making personalized recommendations through nearest-neighbor techniques. First you will learn user-user collaborative filtering, an algorithm that identifies other people with similar tastes to a target user and combines their ratings to make recommendations for that user. You will explore and implement variations of the user-user algorithm, and will explore the benefits and drawbacks of the general approach. Then you will learn the widely-practiced item-item collaborative filtering algorithm, which identifies global product associations from user ratings, but uses these product associations to provide personalized recommendations based on a user's own product ratings.
Note that this course is structured into two-week chunks. The first chunk focuses on User-User Collaborative Filtering; the second chunk on Item-Item Collaborative Filtering. Each chunk has most of the lectures in the first week, and assignments/quizzes and advanced topics in the second week. We encourage learners to treat each two-week chunk as one unit, starting the assignments as soon as they feel they have learned enough to get going.
1 video1 reading
5 videos
2 videos2 readings2 assignments1 programming assignment
6 videos
2 videos2 readings4 assignments1 programming assignment
5 videos1 assignment
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
The University of Minnesota is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation’s most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations.
University of Minnesota
Specialization
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EIT Digital
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University of Minnesota
Course
304 reviews
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Reviewed on Dec 12, 2017
everything best. But technical support in Forum and when a student needs help when he is learning in Vienna alone is the worstthanks very much !
Reviewed on Jul 7, 2019
Great learning experience about collaborative filtering!
Reviewed on Dec 2, 2019
Overall good, except for assignment 2 which was poorly explained on one of the parts
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