Nearest Neighbor Collaborative Filtering

Nearest Neighbor Collaborative Filtering

Nearest Neighbor Collaborative Filtering This course is part of Recommender Systems Specialization Taught in English 22 languages available Some content may not be translated Instructors: Joseph A Konstan +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 4.5 (14

Description

Nearest Neighbor Collaborative Filtering is a popular technique used in recommendation systems to provide personalized recommendations to users. This method is based on the principle that users who have similar preferences in the past are likely to have similar preferences in the future. By leveraging this idea, recommendation systems can effectively recommend items to users based on the preferences of other users who have similar tastes.

One of the key advantages of Nearest Neighbor Collaborative Filtering is its simplicity and ease of implementation. The basic idea behind this technique is to find the nearest neighbors of a target user based on their past interactions with items. These neighbors are users who have rated items similarly to the target user, and their preferences are used to predict the ratings of items that the target user has not yet interacted with. This allows recommendation systems to provide personalized recommendations

Nearest Neighbor Collaborative Filtering

This course is part of Recommender Systems Specialization

Taught in English

Some content may not be translated

Joseph A Konstan
Michael D. Ekstrand

Instructors: Joseph A Konstan

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14 hours (approximately)
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7 quizzes

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