In this article I want to tell you how to do a math activity to explain how some multimedia platforms recommend other movies based on the ones we have already seen

For this I will explain a method called «Content-based recommendation system». It is a small Machine Learning algorithm, simple to implement and explain in a class with high school students and even the last elementary courses.

It is true that many of these platforms already use much more complex and efficient algorithms, but the objective of this activity is to make students see how mathematics is useful for something as everyday as when we sat on the couch to watch a movie in Netflix or HBO.

Look as we explain in these 3 simple pills


What is normalizing a value?

In case you have any doubt about how a value is normalized between defined limits here I put this little explanatory video.


Finally we recommend the movies.


In future articles I will explain how you can recommend a movie that is not within the genre that the user has already seen, it is a bit more complex but surely we can take it to the classroom.

I give you the repository where the notebook made in Python is located

https://github.com/jmcalvomartin/python/tree/master/projects/RecommendationSystems

Also in this article I would like to share the Virtual class that I had the honor of giving to the students of mathematics and physics at the University of Alicante on this practice. A fantastic initiative promoted by Julio Molero, professor of Mathematics at this University