ExamTopics Logo
Mail Us[email protected]
Menu
Amazon Discussions
exam questions

Exam AWS Certified Machine Learning - Specialty All Questions

View all questions & answers for the AWS Certified Machine Learning - Specialty exam
Go to Exam

Exam AWS Certified Machine Learning - Specialty topic 1 question 340 discussion

Exam question from Amazon's AWS Certified Machine Learning - Specialty
Question #: 340
Topic #: 1
[All AWS Certified Machine Learning - Specialty Questions]

A tourism company uses a machine learning (ML) model to make recommendations to customers. The company uses an Amazon SageMaker environment and set hyperparameter tuning completion criteria to MaxNumberOfTrainingJobs.

An ML specialist wants to change the hyperparameter tuning completion criteria. The ML specialist wants to stop tuning immediately after an internal algorithm determines that tuning job is unlikely to improve more than 1% over the objective metric from the best training job.

Which completion criteria will meet this requirement?

  • A. MaxRuntimeInSeconds
  • B. TargetObjectiveMetricValue
  • C. CompleteOnConvergence
  • D. MaxNumberOfTrainingJobsNotImproving
Show Suggested Answer Hide Answer
Suggested Answer: C 🗳️
by georgejinh at Aug. 31, 2024, 7:17 a.m.
Disclaimers:
  • - ExamTopics website is not related to, affiliated with, endorsed or authorized by Amazon.
  • - Trademarks, certification & product names are used for reference only and belong to Amazon.

Comments

Chosen Answer:
This is a voting comment (?). It is better to Upvote an existing comment if you don't have anything to add.
Switch to a voting comment New
Submit Cancel
ef12052
1 month ago
Selected Answer: C
CompleteOnConvergence – A flag to stop tuning after an internal algorithm determines that the tuning job is unlikely to improve more than 1% over the objective metric from the best training job.
upvoted 1 times
...
MultiCloudIronMan
7 months ago
Selected Answer: C
The completion criteria that will meet this requirement is CompleteOnConvergence. This criterion stops the tuning job immediately after an internal algorithm determines that the tuning job is unlikely to improve more than 1% over the objective metric from the best training job
upvoted 1 times
...
Tkhan1
7 months, 1 week ago
Selected Answer: C
C is the correct answer .CompleteOnConvergence – A flag to stop tuning after an internal algorithm determines that the tuning job is unlikely to improve more than 1% over the objective metric from the best training job. https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-progress.html
upvoted 2 times
...
georgejinh
7 months, 3 weeks ago
Selected Answer: C
onvergence detection is a completion criteria that lets automatic model tuning decide when to stop tuning. Generally, automatic model tuning will stop tuning when it estimates that no significant improvement can be achieved.
upvoted 2 times
...
Community vote distribution
A (35%)
C (25%)
B (20%)
Other
Most Voted
A voting comment increases the vote count for the chosen answer by one.

Upvoting a comment with a selected answer will also increase the vote count towards that answer by one. So if you see a comment that you already agree with, you can upvote it instead of posting a new comment.

SaveCancel
exam
Someone Bought Contributor Access for:
SY0-701
London, 1 minute ago