In this section, we are trying to build the best possible recommendation engine. There are two parts to this section:
Our first part covers the basic concepts, such as how the CF and KNN algorithms work, what kind of features we need to choose, and so on. In the second part, we will be implementing the recommendation engine using the KNN and CF algorithm. We will generate the accuracy score as well as the recommendation for books. So let's begin!
In this section, we will understand the concepts of collaborative filtering. This covers a lot of aspects of the recommendation system. So, let's explore CF.
There are two main ...