The Netflix Challenge and what it has to do with math!
Netflix, Amazon, Zalando and others are focusing on one thing in particular when it comes to customer loyalty: good recommendations for new products, movies, clothing, etc. that are customized to the user. To this end, these companies develop recommendation systems that can predict as well as possible what the respective user might like.
To further improve its own recommendation system, Netflix set up a challenge in 2006: The team that could predict at least 10% more accurately which movies a user would like had a chance to win the grand prize of $1 million!
In the workshop you will work with the original data from the Netflix Challenge and develop your own recommendation system. You will apply common strategies from the field of machine learning.
Duration: from 6 hours (including lunch break).
Contents: Data Science, scalar product, vectors, matrices, machine learning.
Previous knowledge: Concept of functions, differential calculus, systems of linear equations.
Participants: Upper level mathematics courses
Created by: Sarah Schönbrodt
Registration: Appointments can be arranged individually by e-mail at KIT or at RWTH Aachen University.
List of publications and talks to this modul:
- Rantzau, L.: Empfehlungssysteme basierend auf Nachbarschaftsmethoden - mathematisch-fachliche Diskussion und Entwicklung digitalen Lernmaterials zur Netflix Challenge für Schüler*innen der Sekundarstufe II, Bachelor thesis, Karlsruhe Institute for Technology, 2021.
- Schönbrodt, S.: Digitales Lernmaterial zur Netflix Challenge (presentation), digital GDM-Month.