To better understand PCA, let's study a movie recommendation use case. Our aim is to build a system that can make personalized movie recommendations to users based on historic user-community movie ratings (note that user viewing history data could also be used for such a system, but this is beyond the scope of this example).
The historic user-community movie ratings data that we will use for our case study has been downloaded from GroupLens, a research laboratory based at the University of Minnesota that collects movie ratings and makes them available for public download at https://grouplens.org/datasets/movielens/. For the purposes of this case study, we have transformed the individual movies and ...
