Amazon AWS

AWS Certified Machine Learning Engineer – Associate

MLA-C01

The AWS Certified Machine Learning Engineer – Associate (MLA-C01) exam validates your skills in building, training, and deploying machine learning models on AWS. It is ideal for those looking to specialize in machine learning.

486 questions 0 views Free
Start Mock Test Timed · Full-length · Scored

Questions 361–370 of 486

Q361

Which AWS service is designed for data labeling?

  • A Amazon SageMaker Ground Truth
  • B AWS DeepRacer
  • C Amazon Rekognition
  • D AWS Glue
Explanation Amazon SageMaker Ground Truth automates data labeling, while others serve different functions.
Q362

A company needs to ensure its machine learning model is regularly updated. Which strategy should it use?

  • A Batch Processing
  • B Online Learning
  • C Data Warehousing
  • D Static Model Deployment
Explanation Online Learning allows for continuous updates, unlike the other options that deal with static or less frequent processes.
Q363

You are configuring an ML workflow in AWS. What happens when you enable AutoML?

  • A Increases manual coding requirements
  • B Reduces feature engineering needs
  • C Requires more data storage
  • D Adds complex model management
Explanation AutoML facilitates automatic feature engineering, while others misrepresent AutoML capabilities.
Q364

Which service is best for building real-time data streaming applications?

  • A Amazon Kinesis
  • B AWS Lambda
  • C Amazon RDS
  • D Amazon EC2
Explanation Amazon Kinesis is designed for real-time data streaming, whereas Lambda is for serverless compute, RDS is for relational databases, and EC2 is for virtual servers.
Q365

A company needs to classify images in real-time based on user uploads. What is the best approach?

  • A Use Amazon Rekognition
  • B Set up an EC2 cluster
  • C Implement a Lambda function
  • D Create a SageMaker model
Explanation Amazon Rekognition specializes in image analysis, while EC2, Lambda, and SageMaker would require more extensive setup and management.
Q366

What happens when you apply batch transformations in AWS SageMaker?

  • A Results are computed in real-time.
  • B Data is processed in bulk.
  • C Model is trained faster.
  • D Latency increases during inference.
Explanation Batch transformations process data in bulk, unlike real-time which is instantaneous, training speed isn't improved, and latency does not generally increase directly due to batch processing.
Q367

Which service allows real-time data processing and analytics in AWS?

  • A Amazon Kinesis
  • B AWS Glue
  • C Amazon S3
  • D Amazon RDS
Explanation Amazon Kinesis is specifically designed for real-time data processing, while the others serve different purposes.
Q368

A company needs to deploy a machine learning model that adjusts dynamically based on incoming data. Which AWS service should they use?

  • A Amazon SageMaker
  • B AWS Lambda
  • C Amazon EMR
  • D AWS Step Functions
Explanation Amazon SageMaker can deploy models that adapt to new data, while the others do not primarily focus on model management.
Q369

You are configuring an IAM policy for specific actions in S3. What happens when a user is denied access?

  • A Access is granted without any message
  • B API calls return an error
  • C User sees a warning notification
  • D Access times out after 5 seconds
Explanation Denied actions in IAM result in API calls returning an error, contrary to the other options.
Q370

Which AWS service would you use for natural language processing?

  • A Amazon Comprehend
  • B Amazon Rekognition
  • C Amazon Lex
  • D AWS Glue
Explanation Amazon Comprehend is designed for NLP tasks, while the others focus on image analysis or data preparation.