Netflix
Presentations about Netflix
Artwork Personalization @Netflix
Netflix Play API - An Evolutionary Architecture
Building Resilience in Production Migrations
Disenchantment: Netflix Titus, its Feisty Team, and Daemons
Interviews
Artwork Personalization @Netflix
What work do you do at Netflix?
I lead one of the Machine Learning and Recommendation teams at Netflix. We're responsible for the end-to-end machine learning that decides what shows up on the Netflix homepage across all our different experiences. When you log into Netflix, my team is responsible for what rows of TV shows and movies you see on the homepage. We select rows and titles to help our members quickly find something great to watch. For example, whether you see Popular on Netflix or Continue Watching at the top of your homepage. We also work on algorithms to personalize the imagery that we display for each title across the experience.
One-third of all Internet traffic at prime-time in North America flows through Netflix systems. How do you measure scale and volume for the amount of recommendations you’re making?
There are over 130 million Netflix subscribers and each home page has many different recommendations on it. Over 80% of what people watch comes from our recommendation systems. Each time you log in, you're typically seeing something new. So we’re serving up a huge number of recommendations to people on a regular basis.