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Quiz12 Amazon Machine Learning and Sagemaker

Question 1:

What limit, if any, is there to the size of your training dataset in Amazon Machine Learning by default?

  • 1TB
  • 100GB
  • 50GB
  • No limit

By default, Amazon ML is limited to 100GB of training data. You can file a support ticket to get this increased, but Amazon ML cannot handle terabyte-scale data.

Question 2:

Is there a limit to the size of the dataset that you can use for training models with Amazon SageMaker? If so, what is the limit?

  • 100GB
  • No fixed limit
  • 1TB
  • 50GB

There are no fixed limits to the size of the dataset you can use for training models with Amazon SageMaker.

Question 3:

The audit team of an organization needs a history of Amazon SageMaker API calls made on their account for security analysis and operational troubleshooting purposes. Which of the following service helps in this regard?

  • CloudTrail
  • Cloud Watch
  • CloudFormation
  • SageMaker Logs

SageMaker outputs its results to both CloudTrail and Cloud Watch, but CloudTrail is specifically designed for auditing purposes.

Question 4:

Which of the following is a new Amazon SageMaker capability that enables machine learning models to train once and run anywhere in the cloud and at the edge?

  • SageMaker Neo
  • SageMaker Search
  • Batch Transform
  • Jupyter Notebooks

Question 5:

A Python developer is planning to develop a machine learning model to predict real estate prices using a Jupyter notebook and train and deploy this model in a high available and scalable manner. The developer wishes to avoid worrying about provisioning sufficient capacity for this model. Which of the following services is best suited for this?

  • Apache Spark
  • Amazon Machine Learning
  • Amazon EMR
  • Amazon SageMaker

SageMaker is the only scalable solution that is both fully managed and uses Jupyter notebooks.