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TensorFlow Extended: An end-to-end machine learning platform for TensorFlow - Robert Crow
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TensorFlow Extended: An end-to-end machine learning platform for TensorFlow
As machine learning evolves from experimentation to serving production workloads, so does the need to effectively manage the end-to-end training and production workflow including model management, versioning, and serving. TFX together with Apache Beam and Apache Flink unlocks new and exciting use cases. Clemens Mewald offers an overview of TensorFlow Extended (TFX), the end-to-end machine learning platform for TensorFlow that powers products across all of Alphabet. Many TFX components rely on the Beam SDK to define portable data processing workflows. This talk explores how Apache Flink runner for Apache Beam Python enables TFX pipelines for production ready machine learning workloads.
Flink Forward San Francisco 2019
#flinkforward
As machine learning evolves from experimentation to serving production workloads, so does the need to effectively manage the end-to-end training and production workflow including model management, versioning, and serving. TFX together with Apache Beam and Apache Flink unlocks new and exciting use cases. Clemens Mewald offers an overview of TensorFlow Extended (TFX), the end-to-end machine learning platform for TensorFlow that powers products across all of Alphabet. Many TFX components rely on the Beam SDK to define portable data processing workflows. This talk explores how Apache Flink runner for Apache Beam Python enables TFX pipelines for production ready machine learning workloads.
Flink Forward San Francisco 2019
#flinkforward
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