Distributed Processing and Components (TensorFlow Extended)

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On today’s episode of TensorFlow Extended hosted by TensorFlow Developer Advocate, Robert Crowe, we’re discussing Distributed Processing and Components. Learn more on Episode 4 of the 5 part series on Real World Machine Learning in Production and a preview for the series finale!

This video is also subtitled in Chinese, Indonesian, Italian, Japanese, Korean, Portuguese, and Spanish.

  1. TensorFlow
  2. Distributed processing and components
  3. apache beam
  4. API
  5. SDK frontends
  6. Java
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Комментарии
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Excellent episodes giving a good picture into understanding TFX ecosystem

mikeisaacs
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Excellent video - very insightful to aid ontop of the tfx homepage website

anando
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are you planning on sharing a fully working example of all of the components described in the series?

azihna
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Excellent episode... Is there a tutorial for running TFX on premise that doesn't use TensorFlow? Any git code examples, books will greatly help
All the TFX examples use Tensorflow. Is TensorFlow pre-requisite for running TFX? I am using pytorch

PavanKumar-rwbr
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How can ExampleValidator generator an anomaly report without having access to the data? The only two inputs are Schema + Statistics from the previous two components.

siddharthkotwal
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Is there one or more books on TFX?
And what about running TFX on premises? Or only at google cloud?

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