How to Build a Recommender System Using TensorFlow

What Is a Recommender System?

A recommender system is a software engine developed to suggest products and services for a given set of customers. While there are multiple ways in which these systems recommend products, the most common is by analyzing a customer's previous purchasing patterns by storing data related to previous purchases, positive and negative reviews, saves/adds to lists, views, and more.

So why do businesses such as Amazon and Netflix spend small fortunes building and improving these systems? Because recommender systems boost sales significantly. By acting as each customer’s personal sales team, recommender systems provide each user with a unique and personalized experience. These systems can help customers identify their favorite movies, books, shows, articles, and more without having to parse through the millions of choices.

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