From Amazon to Netflix to Pinterest, recommendation systems are the cornerstone of a majority of the modern-day billion-dollar industries. However, building recommender systems is not a straightforward task.

What if we can build them in a few lines? Dropping the nitty-gritty details and concentrating on implementing algorithms with more ease is what any data scientist would like to get their hands on. Abstraction is a common trait amongst popular machine learning libraries or frameworks like TensorFlow. Now, the team extends its services to recommender systems as well.

Google has introduced TensorFlow Recommenders (TFRS), an open-source TensorFlow package that makes building, evaluating, and serving sophisticated recommender models easy.

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