Recommendation systems and collaborative filters share a long history. From the early days of primitive recommender engines which utilized specific categorizations with hard-coded results, to current sophisticated recommender engines on various e-commerce platforms, recommender engines have made use of collaborative filters throughout. They are not only easy to understand but are equally simple to implement. Let us take this opportunity to learn more about collaborative filters before we dive into implementation details.
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Fun Fact
Recommender engines surely outdate any known e-commerce platform! Grundy, a virtual librarian, was developed in 1979. It was a system for recommending books to users. It modeled the users based upon certain pre-defined stereotypes and recommended books from a known list for each such category.
