Posts tagged: ml-systems-ml-ops
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Why a good model doesn't necessarily create business value?
A note from the Booking.com case: model performance and business performance are two different things, especially when ML goes into a real product.
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RecSysOps: operating a recommender system after deployment
Notes from Netflix RecSysOps on operating recommender systems: issue detection, issue prediction, diagnosis, and resolution when a recommendation system goes into production.
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Microservice Architecture Patterns for Scalable ML Systems
Practical notes on how to break a Machine Learning system into smaller services to make it easier to deploy, monitor, and scale.
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How Netflix uses ML to optimize streaming quality?
Notes from the Netflix Tech Blog on how Machine Learning is used to predict streaming quality, reduce playback errors, and improve viewer experience.
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What blocks does an ML platform need? Learning from Uber Michelangelo
Analyzing Uber Michelangelo to understand that a production ML platform needs data, training, deployment, prediction, and monitoring.
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