The article discusses Netflix's diverse machine learning applications and the supporting infrastructure built to enhance these use cases. Key areas of focus include content demand modeling, identity resolution, and media processing, illustrating how Netflix employs machine learning to improve recommendations, streamline operations, and evaluate content demand throughout its lifecycle. Noteworthy is the intelligent infrastructure that enables engineering teams to adopt machine learning in traditional products effectively. The article emphasizes practical examples like content knowledge graphs and complex decision-making models, showcasing Netflix’s commitment to leveraging technology for business growth.
We're not going to focus on the machine learning itself, but rather the infrastructure that we built to support all these diverse use cases.
We try to keep a knowledge graph of all actors, movies, and various entities in our space... This is a massively parallel computation matching problem.
This goes all the way from when we first hear a pitch all the way to post-service where we have actual viewing behavior.
Intelligent infrastructure is something that is over the past few years really becoming a big use case.
Collection
[
|
...
]