TensorFlow TFX Team in Munich
SLOT1: TFX: Production ML Pipelines with TensorFlow - Robert Crowe, TensorFlow Developer Advocate, Google
ML development often focuses on metrics, delaying work on deployment and scaling issues. ML development designed for production deployments typically follows a pipeline model, with scaling and maintainability as inherent parts of the design. We examine TensorFlow Extended (TFX), the open source version of the ML infrastructure platform that Google has developed for its own production ML pipelines.
A data scientist and TensorFlow addict, Robert has a passion for helping developers quickly learn what they need to be productive. He’s used TensorFlow since the very early days and is excited about how it’s evolving quickly to become even better than it already is. Before moving to data science Robert led software engineering teams for both large and small companies, always focusing on clean, elegant solutions to well-defined needs. In his spare time Robert sails, surfs occasionally, and raises a family.
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