The collaborative filters we have built thus far are known as memory-based filters. This is because they only make use of similarity metrics to come up with their results. They learn any parameters from the data or assign classes/clusters to the data. In other words, they do not make use of machine learning algorithms.
In this section, we will take a look at some filters that do. We spent an entire chapter looking at various supervised and unsupervised learning techniques. The time has finally come to see them in action and test their potency.
