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%
PRODUCTION MACHINE LEARNING SYSTEMS からの人気レビュー
very good for people who will enter the production stage on machine learning systems
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.
Very practical which was nice. Thank you for adding the Quicklabs that helped a lot.
This course reveals some practical techniques in Production Machine Learning Systems. I like the real world examples introduced in this course.
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Last Updated: September 1, 2015