An introduction to MLOps with TensorFlow Extended (TFX)

Deploying advanced machine learning technology to serve customers and/or business needs requires a rigorous approach and production-ready systems. An ML application in production requires modern software development methodology, as well as issues unique to ML and data science. Hear about the importance of MLOps, the use of ML pipeline architectures for implementing production ML applications, rigorous analysis of model performance and sensitivity, and review Google’s experience with TensorFlow Extended (TFX).

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Speaker: Robert Crowe

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