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Round 2: A Survey of Causal Inference Applications at Netflix

At Netflix, we want to ensure that every current and future member finds content that thrills them today and excites them to come back for more. Causal inference is an essential part of the value that Data Science and Engineering adds towards this mission. We rely heavily on both experimentation and quasi-experimentation to help our teams make the best...

Thu Jun 6, 2024 23:10
The Making of VES: the Cosmos Microservice for Netflix Video Encoding

Liwei Guo, Vinicius Carvalho, Anush Moorthy, Aditya Mavlankar, Lishan ZhuThis is the second post in a multi-part series from Netflix. See here for Part 1 which provides an overview of our efforts in rebuilding the Netflix video processing pipeline with microservices. This blog dives into the details of building our Video Encoding Service (VES), and...

Wed Apr 10, 2024 01:11
Reverse Searching Netflix’s Federated Graph

By Ricky Gardiner, Alex Hutter, and Katie LefevreSince our previous posts regarding Content Engineering’s role in enabling search functionality within Netflix’s federated graph (the first post, where we identify the issue and elaborate on the indexing architecture, and the second post, where we detail how we facilitate querying) there have been significant...

Fri Apr 5, 2024 00:26
Sequential Testing Keeps the World Streaming Netflix Part 2: Counting Processes

Sequential A/B Testing Keeps the World Streaming Netflix Part 2: Counting ProcessesMichael Lindon, Chris Sanden, Vache Shirikian, Yanjun Liu, Minal Mishra, Martin TingleyHave you ever encountered a bug while streaming Netflix? Did your title stop unexpectedly, or not start at all? In the first installment of this blog series on sequential testing, we...

Mon Mar 18, 2024 14:46
Supporting Diverse ML Systems at Netflix

David J. Berg, Romain Cledat, Kayla Seeley, Shashank Srikanth, Chaoying Wang, Darin YuNetflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding. The Machine Learning Platform (MLP) team at Netflix...

Thu Mar 7, 2024 20:32
Bending pause times to your will with Generational ZGC

The surprising and not so surprising benefits of generations in the Z Garbage Collector.By Danny Thomas, JVM Ecosystem TeamThe latest long term support release of the JDK delivers generational support for the Z Garbage Collector. Netflix has switched by default from G1 to Generational ZGC on JDK 21 and later, because of the significant benefits of concurrent...

Wed Mar 6, 2024 03:34

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