In this section, we are going to discuss how to build a product recommendation system using R. More specifically, we will be learning how to implement a collaborative filtering algorithm in R using the dplyr, reshape2, and coop packages. For those readers who would like to use Python instead of R for this exercise, you can go to the previous section. We will start this section by analyzing some e-commerce business data and then discuss the two approaches to building a product recommendation system with collaborative filtering.
For this exercise, we will be using one of the publicly available datasets from the UCI Machine Learning Repository, which can be found at: http://archive.ics.uci.edu/ml/datasets/online+retail#. You can go to this link and download the data, available in Microsoft Excel format, named Online Retail.xlsx....