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Exam AWS Certified Machine Learning - Specialty topic 1 question 172 discussion

Exam question from Amazon's AWS Certified Machine Learning - Specialty
Question #: 172
Topic #: 1
[All AWS Certified Machine Learning - Specialty Questions]

A data scientist has a dataset of machine part images stored in Amazon Elastic File System (Amazon EFS). The data scientist needs to use Amazon SageMaker to create and train an image classification machine learning model based on this dataset. Because of budget and time constraints, management wants the data scientist to create and train a model with the least number of steps and integration work required.
How should the data scientist meet these requirements?

  • A. Mount the EFS file system to a SageMaker notebook and run a script that copies the data to an Amazon FSx for Lustre file system. Run the SageMaker training job with the FSx for Lustre file system as the data source.
  • B. Launch a transient Amazon EMR cluster. Configure steps to mount the EFS file system and copy the data to an Amazon S3 bucket by using S3DistCp. Run the SageMaker training job with Amazon S3 as the data source.
  • C. Mount the EFS file system to an Amazon EC2 instance and use the AWS CLI to copy the data to an Amazon S3 bucket. Run the SageMaker training job with Amazon S3 as the data source.
  • D. Run a SageMaker training job with an EFS file system as the data source.
Show Suggested Answer Hide Answer
Suggested Answer: D 🗳️
by cron0001 at April 29, 2022, 11:12 a.m.
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cron0001
Highly Voted 2 years, 6 months ago
Selected Answer: D
Should be D according to the following article https://aws.amazon.com/blogs/machine-learning/speed-up-training-on-amazon-sagemaker-using-amazon-efs-or-amazon-fsx-for-lustre-file-systems/
upvoted 12 times
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Sharath1783
Highly Voted 1 year, 1 month ago
Selected Answer: D
SageMaker Noteboob instances can take input data directly from below, 1. AWS S3 2. Elastic File System (EFS) 3. FSx for Lustre file system Since the question is only regarding less coding effort and does not concern high availability or high performance, Option D would be good
upvoted 5 times
confusedyeti69
7 months, 1 week ago
boobies
upvoted 1 times
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AIWave
Most Recent 8 months, 1 week ago
Selected Answer: D
Using Amazon SageMaker for training, you can utilize an Amazon EFS as your data source as long as the data already resides in Amazon EFS before starting the training job. This option requires least integration work.
upvoted 2 times
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jopaca1216
1 year, 1 month ago
My God, the answer is not D!!! Using EFS for Lustre reduces the start-up time by eliminating the data download step of the training process and leveraging the various performance and throughput benefits of the file system to execute the training job faster. So, A IS the correct !!!
upvoted 1 times
thuyeinaung
11 months, 1 week ago
"with the least number of steps and integration work required"
upvoted 1 times
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teka112233
1 year, 1 month ago
Selected Answer: D
the management wants the data scientist to create and train a model with the least number of steps and integration work required, (this is the keyword) so there is no need to include more things than sagemaker and EFS which make option D is the most suitable
upvoted 1 times
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Mickey321
1 year, 3 months ago
Selected Answer: D
This option allows the data scientist to use the existing dataset in EFS without copying or moving it to another storage service. It also minimizes the number of steps and integration work required, as SageMaker supports EFS as a data source for training jobs. This option is also cost-effective and time-efficient, as it avoids additional charges and delays associated with data transfer and storage.
upvoted 1 times
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Mllb
1 year, 7 months ago
Selected Answer: D
Less effort, then D
upvoted 3 times
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Jerry84
1 year, 9 months ago
Selected Answer: D
“When you create a training job, you specify the location of a training dataset and an input mode for accessing the dataset. For data location, Amazon SageMaker supports Amazon Simple Storage Service (Amazon S3), Amazon Elastic File System (Amazon EFS), and Amazon FSx for Lustre. ” https://docs.aws.amazon.com/sagemaker/latest/dg/model-access-training-data.html
upvoted 2 times
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srikanth923
2 years ago
Selected Answer: D
https://aws.amazon.com/blogs/machine-learning/mount-an-efs-file-system-to-an-amazon-sagemaker-notebook-with-lifecycle-configurations/
upvoted 3 times
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ckkobe24
2 years, 5 months ago
Amazon SageMaker now supports Amazon Elastic File System (Amazon EFS) and Amazon FSx for Lustre file systems as data sources for training machine learning models on SageMaker. then why not select D ??
upvoted 4 times
jhonivy
1 year, 9 months ago
Time constraints. A is the right answer for this question
upvoted 1 times
wolfsong
1 year, 8 months ago
A is not the right answer. It's D. - A requires this setup: EFS -> Lustre -> Sagemaker. - D requires this setup: EFS -> Sagemaker It's obviously not A.
upvoted 2 times
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