October 2019
Intermediate to advanced
520 pages
13h 5m
English
Content preview from Professional Cloud Architect – Google Cloud Certification Guide
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ML Engine scale tiers
Running a training job on Cloud ML requires you to specify machines that you require for the job.
You can choose from predefined clusters (scale tiers) or use a custom configuration. With a custom configuration, you need to specify what machines your cluster will consist of. Note that there are different types of servers that build the cluster:
- Masters: These manage other nodes
- Workers: These work on a chunk of a training job
- Parameter servers: These manage the shared model state
There are a couple of cluster options you can choose from:
- BASIC: One worker instance.
- STANDARD_1: One master instance, plus four workers and three parameter servers.
- PREMIUM_1: One master instance, plus 19 workers and 11 parameter servers. ...
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