I hope that you are now excited about the amazing possibilities offered by the recommender systems that we've built. The techniques we've learned will provide you with a tremendous amount of data-taming prowess and practical abilities that you can already apply in your projects.
However, there is more to recommendation systems than that. Due to their large-scale applications in recent years, as an efficient solution to the information overload caused by the abundance of offerings on online platforms, recommenders have received a lot of attention, with new algorithms being developed at a rapid pace. In fact, all the algorithms that we studied in the previous chapter are part of a single category, called memory-basedrecommenders. Besides these, there's another very important class or recommender, which is known as model-based.
In this chapter, we'll learn about them. We will discuss the following topics:
- Memory-based versus model-based recommendation...