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.
Об этом курсе
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Лучшие отзывы о курсе PRODUCTION MACHINE LEARNING SYSTEMS
Unlike pure technical courses, this one specially packs you with knowledge that you may find yourself face to. The course is really well designed and the content is crystal clear, just Awesome !
Excellent overview of designing real-world ML systems. Some of the labs are daunting, but the emphasis is showing you what can be achieved, rather than achieving mastery within 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
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
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