This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators.
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- 5 stars70,46 %
- 4 stars21,38 %
- 3 stars5,86 %
- 2 stars1,52 %
- 1 star0,76 %
Principales reseñas sobre PRODUCTION MACHINE LEARNING SYSTEMS
I did not realize the many aspects to consider implementing a Production ML system. This course presents all of them and provides guidance for evaluating alternative
very good information. Lot of unknown facts in ML are brought up in the course.
It is very good course, gives good overview over large ML systems on cloud, a lot of examples from real implementations gives good understunding about problematics in projects realisations
direct to the point practical guidance for dev stage prod sequence
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