PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #75
You recently designed and built a custom neural network that uses critical dependencies specific to your organization's framework. You need to train the model using a managed training service on…
The correct answer is C. Build your custom containers to run distributed training jobs on AI Platform Training. By running your machine learning (ML) training job in a custom container, you can use ML frameworks, non-ML dependencies, libraries, and binaries that are not otherwise supported on Model and your data are too large to fit in memory on a single machine hence distributed…
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Options
- AUse a built-in model available on AI Platform Training.
- BBuild your custom container to run jobs on AI Platform Training.
- CBuild your custom containers to run distributed training jobs on AI Platform Training.
- DReconfigure your code to a ML framework with dependencies that are supported by AI Platform
How the community answered
(23 responses)- A4% (1)
- B4% (1)
- C83% (19)
- D9% (2)
Explanation
By running your machine learning (ML) training job in a custom container, you can use ML frameworks, non-ML dependencies, libraries, and binaries that are not otherwise supported on Model and your data are too large to fit in memory on a single machine hence distributed training https://cloud.google.com/vertex-ai/docs/training/containers-overview
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