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Building Similarity Based Recommendation System

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Welcome to this 1-hour project-based course on Building Similarity Based Recommendation System. In this project, you will learn how similarity based collaborative filtering recommendation systems work, how you can collect data for building such systems. You will learn what are some different ways you to compute similarity between users and recommend items based on products interacted by other similar users. You will learn to create user item interactions matrix from the original dataset and also how to recommend items to a new user who does not have any historical interactions with the items. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

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Enhance your personal development skills with our engaging 1-hour project-based course on Building Similarity Based Recommendation Systems. Ideal for intermediate learners, this course offers a hands-on approach to mastering the techniques used to create recommendation systems that leverage similarity metrics. Guided by expert instructors from Coursera, you’ll dive into practical, real-world applications of this technology. Best of all, this course is available for free, making it an accessible resource for anyone looking to expand their knowledge in this dynamic field. Join us and take a significant step forward in your personal and professional growth.