Topic 1 Question 342
A media company is building a computer vision model to analyze images that are on social media. The model consists of CNNs that the company trained by using images that the company stores in Amazon S3. The company used an Amazon SageMaker training job in File mode with a single Amazon EC2 On-Demand Instance.
Every day, the company updates the model by using about 10,000 images that the company has collected in the last 24 hours. The company configures training with only one epoch. The company wants to speed up training and lower costs without the need to make any code changes.
Which solution will meet these requirements?
Instead of File mode, configure the SageMaker training job to use Pipe mode. Ingest the data from a pipe.
Instead of File mode, configure the SageMaker training job to use FastFile mode with no other changes.
Instead of On-Demand Instances, configure the SageMaker training job to use Spot Instances. Make no other changes,
Instead of On-Demand Instances, configure the SageMaker training job to use Spot Instances, implement model checkpoints.
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コメント(7)
- 正解だと思う選択肢: B
FastFile mode provides the best balance
👍 3GS_772024/09/07 - 正解だと思う選択肢: B
I think B, fastfile is built on pile and offers more
👍 2MultiCloudIronMan2024/09/23 - 正解だと思う選択肢: D
This option combines the cost savings of Spot Instances with the reliability of model checkpoints. Checkpointing allows the training job to resume from the last saved state in case of interruption, making it a robust choice for maintaining progress without losing work. While it suggests implementing checkpoints, the setup for checkpointing can typically be done with minimal changes, depending on the existing training setup.
👍 27f1fe732024/10/26
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