Recommender systems are ubiquitous in today's world. Be it movie recommendations on Netflix or product recommendations on Amazon, recommender systems are making a significant impact. Recommender systems can be broadly classified into content-based filtering systems, collaborative filtering systems, and latent factor-based filtering recommender systems. Content-based filtering relies on hand-coding features for the items based on their content. Based on how the users have rated existing items, a user profile is created and the ranks provided by the user are given to those items:
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As we can see in the preceding diagram (Figure 6.1), User A has bought books named Deep Learning and Neural Networks. Since the content of the book Artificial Intelligence is similar to the two books, the content-based...