Full implementation is complex: it needs advanced linear algebra.

Types of Recommender Systems:

  • Content based. Focus on the attributes of the items: the usual “related items”.
  • Collaborative filter (CF). Uses “wisdom of the crowd” to recommend items: eg Amazon. CF is most used on content based systems. It can do feature learning by itself.
    The Movie land dataset of movies to study.  These methods can be:
    – Memory based CF: singular value decomposition.
    – Collaborative CF: computing cosine similarity.