In this chapter, we learned about what a recommendation system is, including the different types of recommendation systems, such as collaborative-based, content-based, demographic-based, utility-based, knowledge-based, and a hybrid approach. We then looked at different tools that are commercially available that have more advanced algorithms that can boost your store's user experience and sales.
We then moved on to something more practical: building our own book recommendation system. We built our model-based on three datasets: books, users, and ratings. We started off by loading the dataset in our program and verifying it by outputting different print statements related to a dataset. We also used the matplotlib library to visually analyze the data. We then applied different algorithms in order to recommend books to our users, such as top-rated books, the most...
