AWS Certified Machine Learning Specialty (MLS-C01)

The AWS Certified Machine Learning Specialty (MLS-C01) were last updated on today.
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  • Viewing questions 41-45 out of 285 questions
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Topic 1 - Exam A

Question #41 Topic 1

An online reseller has a large, multi-column dataset with one column missing 30% of its data. A Machine Learning Specialist believes that certain columns in the dataset could be used to reconstruct the missing data. Which reconstruction approach should the Specialist use to preserve the integrity of the dataset?

  • A Listwise deletion
  • B Last observation carried forward
  • C Multiple imputation
  • D Mean substitution
Suggested Answer: C
NOTE: Reference: https://worldwidescience.org/topicpages/i/imputing+missing+values.html
Question #42 Topic 1

A Machine Learning Specialist is building a model that will perform time series forecasting using Amazon SageMaker. The Specialist has finished training the model and is now planning to perform load testing on the endpoint so they can configure Auto Scaling for the model variant. Which approach will allow the Specialist to review the latency, memory utilization, and CPU utilization during the load test?

  • A Review SageMaker logs that have been written to Amazon S3 by leveraging Amazon Athena and Amazon QuickSight to visualize logs as they are being produced.
  • B Generate an Amazon CloudWatch dashboard to create a single view for the latency, memory utilization, and CPU utilization metrics that are outputted by Amazon SageMaker.
  • C Build custom Amazon CloudWatch Logs and then leverage Amazon ES and Kibana to query and visualize the log data as it is generated by Amazon SageMaker.
  • D Send Amazon CloudWatch Logs that were generated by Amazon SageMaker to Amazon ES and use Kibana to query and visualize the log data.
Suggested Answer: B
NOTE: Reference: https://docs.aws.amazon.com/sagemaker/latest/dg/monitoring-cloudwatch.html
Question #43 Topic 1

A Machine Learning Specialist is deciding between building a naive Bayesian model or a full Bayesian network for a classification problem. The Specialist computes the Pearson correlation coefficients between each feature and finds that their absolute values range between 0.1 to 0.95. Which model describes the underlying data in this situation?

  • A A naive Bayesian model, since the features are all conditionally independent.
  • B A full Bayesian network, since the features are all conditionally independent.
  • C A naive Bayesian model, since some of the features are statistically dependent.
  • D A full Bayesian network, since some of the features are statistically dependent.
Suggested Answer: C
NOTE:
Question #44 Topic 1

A monitoring service generates 1 TB of scale metrics record data every minute. A Research team performs queries on this data using Amazon Athena. The queries run slowly due to the large volume of data, and the team requires better performance. How should the records be stored in Amazon S3 to improve query performance?

  • A CSV files
  • B Parquet files
  • C Compressed JSON
  • D RecordIO
Suggested Answer: B
NOTE:
Question #45 Topic 1

A Machine Learning Specialist wants to bring a custom algorithm to Amazon SageMaker. The Specialist implements the algorithm in a Docker container supported by Amazon SageMaker. How should the Specialist package the Docker container so that Amazon SageMaker can launch the training correctly?

  • A Modify the bash_profile file in the container and add a bash command to start the training program
  • B Use CMD config in the Dockerfile to add the training program as a CMD of the image
  • C Configure the training program as an ENTRYPOINT named train
  • D Copy the training program to directory /opt/ml/train
Suggested Answer: B
NOTE: