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.
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
- 5 stars70.30%
- 4 stars21.59%
- 3 stars5.83%
- 2 stars1.51%
- 1 star0.75%
PRODUCTION MACHINE LEARNING SYSTEMS からの人気レビュー
The course provides insight into applying Machine Learning system in actual environment, with real-life examples and lab assistance.
Really focuses on topics for building production ML Systems
very very useful topics to improve and deploying machine learning for productions.
It was bit hard course but lab work was great and learn many production level consideration for ml systems.
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Last Updated: September 1, 2015