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WeAreNetflix

S1: Machine Learning Infrastructure at Netflix

Jul 27, 2018
The podcast discusses improving infrastructure at Netflix and empowering data scientists, their operating approach and culture, the importance of machine learning models, the algorithms used in the Netflix app, video encoding versions and adaptive streaming, and personalization and collaboration in ML infrastructure.
53:43

Podcast summary created with Snipd AI

Quick takeaways

  • Netflix leverages technologies like Metaflow and Titus to empower data scientists and improve collaboration.
  • Netflix is exploring the use of reinforcement learning to enhance the streaming quality for users by training machine learning models to determine the appropriate video bitrate based on real-time network conditions.

Deep dives

Machine Learning Infrastructure at Netflix

Machine learning infrastructure at Netflix is focused on scaling and making data scientists more productive. They leverage technologies like Metaflow and Titus to empower data scientists to build their own microservices and enable collaboration. The infrastructure includes tools for data preparation, feature engineering, training models, and orchestrating workflows. They also use EV cache for high-throughput, low-latency caching, and leverage AWS for their control plane. They are working on challenges such as improving the streaming experience, content exploration, and studio production. Feedback and a culture of learning are emphasized, enabling continuous improvement and innovation.

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