Does Netflix use machine learning?
Does Netflix use machine learning?
So this isn’t exactly a FinTech specific issue. But, we do cover the News here! And News encompasses more than just the FinTech world. We feel Machine Learning is a relevant enough subject for us to cover. As its a major part of the FinTech world.
Well getting back to Netflix…
According to GeeksforGeeks:
“Netflix uses machine learning in almost all the facets of its working to provide a seamless experience for users. After all, the data collected by Netflix is huge which includes both the explicit data such as thumbs up or thumbs down for a movie and even implicit data such as data and location where users watch a particular content, the time they watch it for, what device they use, whether they binge-watch it or not, their content choices, online behavior, etc. All this data can be used for machine learning. That ultimately improves the bottom line i.e. gets more subscribers for Netflix!”
At the beginning of building the product, Netflix is building the product to attract more customers.
Developers choose to use machine learning as tools.
Using machine learning algorithms, it can recognize and categorize all the pictures for movies which includes billions of movies in the databases. Based on the movie that the customer selected previously, a machine learning algorithm can push the relevant movies to the customer. It increases the opportunity for customers to select the movie faster and stay on the platform.
The tricky part is how the machine learning algorithm really categorizes the films. The algorithm studies the main characters in the film. And those actors are categorized as comic, romantic, etc.
In conclusion, Netflix continues as a Machine Learning major player.
Moreover, as people know, the algorithm make mistakes too. So Netflix still has a lot of work to do.
For example, a film categorized as funny or romantic depending on which actor recognized in the film.
As a result, a customer might want a romantic movie or an action movie, but the algorithm may suggest the same movie since different actors in the same film can lead to different results in categorization.
Another issue is that the algorithm can change the view rate of the movies. If a movie becomes categorized in a lot of different characterizations, it has a larger chance to show up to a larger base of customers. This can be unfair in some situations.
