top of page

NETFLIX MOVIE RECOMMENDATION

A recommendation system to recommend movies to users based on the ratings given to different movies by the users.

In this case study, we saw three different ways of building recommendation systems:


  • rank-based using averages

  • similarity-based collaborative filtering

  • model-based (matrix factorization) collaborative filtering


We also understood advantages/disadvantages of these recommendation systems and when to use which kind of recommendation systems. Once we build these recommendation systems, we can use A/B Testing to measure the effectiveness of these systems.

bottom of page