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:
![](https://static.packt-cdn.com/products/9781788996921/graphics/assets/eaa4391a-b8cf-42ce-bad4-c4977e83bdbc.png)
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...