Machine Learning and Netflix
Netflix is well-known for its capability of utilizing cloud services and instituting machine learning technology. The company is building machine learning systems to attract more customers. Developers have chosen to use the machine learning systems as tools. In early 2016, Netflix mentioned that a customer often makes decisions on what movie to watch in just 90 seconds. If they can’t find a movie within that timespan, they would just leave the platform. In its early stages, Netflix knew it was important to figure out how to target individual customers for higher retention rates. Machine learning comes in with perfect timing for dealing with this issue.
Using machine learning algorithms, Netflix can recognize and categorize all of its movies. Based on the movies that the customer has watched previously, the machine learning algorithm can offer relevant movies as suggestions to be watched next. This increases the likelihood of the customer retaining interest in the platform. In this case, the algorithm’s primary use is to recognize pictures of films and categorize them. When customers are selecting movies, the machine learning algorithm will offer films based on a customer’s viewing history.
The tricky part of this is how the machine learning algorithm categorizes the films. The algorithm studies the main characters in the film and what categories these characters are affiliated with. For instance, in a movie featuring Batman and Robin, the machine would label these two characters as superheroes, thus categorizing the movie as a superhero film.
Obviously, the algorithm can make mistakes too. For example, a film can be categorized as funny or romantic depending on which actors the machine chooses to recognize. A customer looking for romantic movies might be misled by an algorithm. Another issue is that the algorithm can change the viewing rate of certain movies. If a movie can fit under multiple categories, it has a larger chance to be viewed by consumers. This can be unfair in some situations.
All in all, the machine learning algorithm has helped Netflix attract more users. At the same time, it saves existing users time to find their favorite movies and shows. Developers are taking time to revisit the algorithm and help make it fair for everyone. The machine learning algorithm makes sets Netflix apart from traditional TV platforms; it helps Netflix to better target individual customers and provide personalized content. Traditional TV platforms cannot provide this. These capabilities have contributed to the rise in Netflix’s popularity, demonstrating the power of machine learning.
Written by Yan Zimo, Edited by Michael Ding, Rachel Weissman & Alexander Fleiss
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