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Amazon AWS-Certified-Machine-Learning-Specialty Valid Test Syllabus - Valid AWS-Certified-Machine-Learning-Specialty Learning Materials
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NEW QUESTION 26
A Machine Learning Specialist is developing a custom video recommendation model for an application. The dataset used to train this model is very large with millions of data points and is hosted in an Amazon S3 bucket. The Specialist wants to avoid loading all of this data onto an Amazon SageMaker notebook instance because it would take hours to move and will exceed the attached 5 GB Amazon EBS volume on the notebook instance.
Which approach allows the Specialist to use all the data to train the model?

  • A. Load a smaller subset of the data into the SageMaker notebook and tram locally. Confirm that the training code is executing and the model parameters seem reasonable. Launch an Amazon EC2 instance with an AWS Deep Learning AMI and attach the S3 bucket to train the full dataset.
  • B. Use AWS Glue to train a model using a small subset of the data to confirm that the data will be compatible with Amazon SageMaker. Initiate a SageMaker training job using the full dataset from the S3 bucket using Pipe input mode.
  • C. Load a smaller subset of the data into the SageMaker notebook and train locally. Confirm that the training code is executing and the model parameters seem reasonable. Initiate a SageMaker training job using the full dataset from the S3 bucket using Pipe input mode.
  • D. Launch an Amazon EC2 instance with an AWS Deep Learning AMI and attach the S3 bucket to the instance. Train on a small amount of the data to verify the training code and hyperparameters. Go back to Amazon SageMaker and train using the full dataset

Answer: A

 

NEW QUESTION 27
A company is running a machine learning prediction service that generates 100 TB of predictions every day. A Machine Learning Specialist must generate a visualization of the daily precision- recall curve from the predictions, and forward a read-only version to the Business team.
Which solution requires the LEAST coding effort?

  • A. Run a daily Amazon EMR workflow to generate precision-recall data, and save the results in Amazon S3. Visualize the arrays in Amazon QuickSight, and publish them in a dashboard shared with the Business team.
  • B. Generate daily precision-recall data in Amazon QuickSight, and publish the results in a dashboard shared with the Business team.
  • C. Generate daily precision-recall data in Amazon ES, and publish the results in a dashboard shared with the Business team.
  • D. Run daily Amazon EMR workflow to generate precision-recall data, and save the results in Amazon S3.
    Give the Business team read-only access to S3.

Answer: A

 

NEW QUESTION 28
A Machine Learning Specialist is using an Amazon SageMaker notebook instance in a private subnet of a corporate VPC. The ML Specialist has important data stored on the Amazon SageMaker notebook instance's Amazon EBS volume, and needs to take a snapshot of that EBS volume. However, the ML Specialist cannot find the Amazon SageMaker notebook instance's EBS volume or Amazon EC2 instance within the VPC.
Why is the ML Specialist not seeing the instance visible in the VPC?

  • A. Amazon SageMaker notebook instances are based on AWS ECS instances running within AWS service accounts.
  • B. Amazon SageMaker notebook instances are based on EC2 instances running within AWS service accounts.
  • C. Amazon SageMaker notebook instances are based on the Amazon ECS service within customer accounts.
  • D. Amazon SageMaker notebook instances are based on the EC2 instances within the customer account, but they run outside of VPCs.

Answer: B

Explanation:
Explanation/Reference: https://docs.aws.amazon.com/sagemaker/latest/dg/gs-setup-working-env.html

 

NEW QUESTION 29
An employee found a video clip with audio on a company's social media feed. The language used in the video is Spanish. English is the employee's first language, and they do not understand Spanish. The employee wants to do a sentiment analysis.
What combination of services is the MOST efficient to accomplish the task?

  • A. Amazon Transcribe, Amazon Translate and Amazon SageMaker BlazingText
  • B. Amazon Transcribe, Amazon Comprehend, and Amazon SageMaker seq2seq
  • C. Amazon Transcribe, Amazon Translate, and Amazon Comprehend
  • D. Amazon Transcribe, Amazon Translate, and Amazon SageMaker Neural Topic Model (NTM)

Answer: C

Explanation:
https://aws.amazon.com/getting-started/hands-on/analyze-sentiment-comprehend/

 

NEW QUESTION 30
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