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Exam AWS Certified Machine Learning - Specialty topic 1 question 332 discussion

Exam question from Amazon's AWS Certified Machine Learning - Specialty
Question #: 332
Topic #: 1
[All AWS Certified Machine Learning - Specialty Questions]

A data scientist is implementing a deep learning neural network model for an object detection task on images. The data scientist wants to experiment with a large number of parallel hyperparameter tuning jobs to find hyperparameters that optimize compute time.

The data scientist must ensure that jobs that underperform are stopped. The data scientist must allocate computational resources to well-performing hyperparameter configurations. The data scientist is using the hyperparameter tuning job to tune the stochastic gradient descent (SGD) learning rate, momentum, epoch, and mini-batch size.

Which technique will meet these requirements with LEAST computational time?

  • A. Grid search
  • B. Random search
  • C. Bayesian optimization
  • D. Hyperband
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Suggested Answer: D 🗳️
by KAST_424 at March 14, 2024, 7:38 p.m.
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MultiCloudIronMan
6 months ago
Selected Answer: D
Efficient Resource Allocation: Hyperband is designed to allocate computational resources efficiently by dynamically stopping underperforming configurations and focusing on the more promising ones
upvoted 2 times
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vkbajoria
1 year, 1 month ago
Selected Answer: D
Hyperband is he answer
upvoted 1 times
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butaman
1 year, 1 month ago
Selected Answer: D
The best technique for the data scientist’s requirements is Hyperband. It’s designed for a large number of experiments, stops low-performance models early, and allocates more resources to high-performance models. This reduces computational time compared to Grid Search, Random Search, and Bayesian Optimization which don’t have these features.
upvoted 1 times
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AIWave
1 year, 1 month ago
Selected Answer: D
Hyperband involves training multiple models with different hyperparameter configurations , eliminating poorly performing ones and allocating resources to promising ones.
upvoted 1 times
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KAST_424
1 year, 1 month ago
Selected Answer: D
. Hyperband: This technique is a bandit-based approach that allocates resources efficiently by running multiple configurations in parallel with varying durations. It eliminates poorly performing configurations early and focuses resources on promising ones, making it ideal for minimizing compute time.
upvoted 2 times
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