Production Machine Learning Systems
Production Machine Learning Systems
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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.
This is the second course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Image Understanding with TensorFlow on Google Cloud course.
课程信息
目标
- Compare static versus dynamic training and inference
- Manage model dependencies
- Set up distributed training for fault tolerance, replication, and more
- Export models for portability
前提条件
Basic SQL, familiarity with Python and TensorFlow
受众
Data Engineers and programmers interested in learning how to apply machine learning in practice.
Anyone interested in learning how to leverage machine learning in their enterprise.
支持的语言
English, español (Latinoamérica), français, 日本語, and português (Brasil)
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学完一门课程后，您将获得结业徽章。徽章可在个人资料中供查看，还可在社交网络上分享。
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