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Amazon Web Services Updated MLS-C01 Exam Questions and Answers by rueben

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Amazon Web Services MLS-C01 Exam Overview :

Exam Name: AWS Certified Machine Learning - Specialty
Exam Code: MLS-C01 Dumps
Vendor: Amazon Web Services Certification: AWS Certified Specialty
Questions: 322 Q&A's Shared By: rueben
Question 40

A data scientist is trying to improve the accuracy of a neural network classification model. The data scientist wants to run a large hyperparameter tuning job in Amazon SageMaker.

However, previous smaller tuning jobs on the same model often ran for several weeks. The ML specialist wants to reduce the computation time required to run the tuning job.

Which actions will MOST reduce the computation time for the hyperparameter tuning job? (Select TWO.)

Options:

A.

Use the Hyperband tuning strategy.

B.

Increase the number of hyperparameters.

C.

Set a lower value for the MaxNumberOfTrainingJobs parameter.

D.

Use the grid search tuning strategy

E.

Set a lower value for the MaxParallelTrainingJobs parameter.

Discussion
Question 41

A data scientist is building a new model for an ecommerce company. The model will predict how many minutes it will take to deliver a package.

During model training, the data scientist needs to evaluate model performance.

Which metrics should the data scientist use to meet this requirement? (Select TWO.)

Options:

A.

InferenceLatency

B.

Mean squared error (MSE)

C.

Root mean squared error (RMSE)

D.

Precision

E.

Accuracy

Discussion
Question 42

A Machine Learning Specialist is packaging a custom ResNet model into a Docker container so the company can leverage Amazon SageMaker for training. The Specialist is using Amazon EC2 P3 instances to train the model and needs to properly configure the Docker container to leverage the NVIDIA GPUs.

What does the Specialist need to do?

Options:

A.

Bundle the NVIDIA drivers with the Docker image.

B.

Build the Docker container to be NVIDIA-Docker compatible.

C.

Organize the Docker container's file structure to execute on GPU instances.

D.

Set the GPU flag in the Amazon SageMaker CreateTrainingJob request body

Discussion
Question 43

A company wants to conduct targeted marketing to sell solar panels to homeowners. The company wants to use machine learning (ML) technologies to identify which houses already have solar panels. The company has collected 8,000 satellite images as training data and will use Amazon SageMaker Ground Truth to label the data.

The company has a small internal team that is working on the project. The internal team has no ML expertise and no ML experience.

Which solution will meet these requirements with the LEAST amount of effort from the internal team?

Options:

A.

Set up a private workforce that consists of the internal team. Use the private workforce and the SageMaker Ground Truth active learning feature to label the data. Use Amazon Rekognition Custom Labels for model training and hosting.

B.

Set up a private workforce that consists of the internal team. Use the private workforce to label the data. Use Amazon Rekognition Custom Labels for model training and hosting.

C.

Set up a private workforce that consists of the internal team. Use the private workforce and the SageMaker Ground Truth active learning feature to label the data. Use the SageMaker Object Detection algorithm to train a model. Use SageMaker batch transform for inference.

D.

Set up a public workforce. Use the public workforce to label the data. Use the SageMaker Object Detection algorithm to train a model. Use SageMaker batch transform for inference.

Discussion
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