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Updated in [July 27th, 2023]
This 1-hour project-based course provides learners with an introduction to Building Similarity Based Recommendation Systems. Participants will learn how these systems work, how to collect data for building them, and how to compute similarity between users and recommend items based on products interacted by other similar users. Additionally, learners will create user item interactions matrices from the original dataset and learn how to recommend items to a new user who does not have any historical interactions with the items. This course is best suited for learners based in the North America region, though efforts are being made to provide the same experience in other regions.