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 351–360 of 486

Q351

What happens when you increase the instance size for an ML training job in SageMaker?

  • A Costs decrease immediately
  • B Training time may decrease
  • C Data privacy improves
  • D Model accuracy improves instantly
Explanation Increasing instance size may decrease training time, while the other options are not directly related to instance size.
Q352

Which service is best for real-time data streaming in AWS?

  • A Amazon Kinesis
  • B AWS Lambda
  • C Amazon S3
  • D Amazon EC2
Explanation Amazon Kinesis is specifically designed for real-time data streaming, while the others serve different purposes.
Q353

A company needs to automatically scale its machine learning workload based on demand. Which AWS service should it use?

  • A AWS Lambda
  • B Amazon SageMaker
  • C AWS Auto Scaling
  • D AWS Batch
Explanation AWS Auto Scaling is designed for automatically scaling resources based on demand, while the others do not directly handle workload scaling.
Q354

What happens when you invoke a SageMaker endpoint with a missing input feature?

  • A Returns an error
  • B Uses default value
  • C Suppresses feature influence
  • D Applies random forests
Explanation Returning an error occurs because inputs must match the trained model's expected features, while the other options are incorrect assumptions.
Q355

Which service allows real-time stream processing of data?

  • A Amazon Kinesis
  • B AWS S3
  • C Amazon RDS
  • D AWS IAM
Explanation Amazon Kinesis is designed for real-time analytics, while the others serve different purposes.
Q356

A company needs to train a model but has limited data resources. Which AWS service can help augment this data?

  • A Amazon SageMaker Ground Truth
  • B AWS Glue
  • C Amazon Lex
  • D Amazon Polly
Explanation Amazon SageMaker Ground Truth helps create labeled datasets; the other options do not provide data augmentation techniques.
Q357

You are configuring a prediction endpoint in Amazon SageMaker. What should you ensure is enabled for better performance?

  • A Integrated development environment
  • B Multi-model endpoint
  • C Data versioning
  • D Checkpointing for models
Explanation Multi-model endpoints in SageMaker optimize costs and performance for serving multiple models concurrently, unlike the other options.
Q358

Which AWS service is best for real-time data processing?

  • A Amazon Kinesis
  • B Amazon S3
  • C AWS Lambda
  • D Amazon RDS
Explanation Amazon Kinesis is specifically designed for real-time data processing, unlike the others which serve different purposes.
Q359

A company needs to improve image classification accuracy. What should they first consider?

  • A Increasing batch size
  • B Adjusting learning rate
  • C Collecting more training data
  • D Changing the optimizer used
Explanation Collecting more training data can significantly improve model accuracy, more than simply adjusting settings.
Q360

You are configuring an Amazon SageMaker training job. What happens if the "MaxRuntimeInSeconds" is exceeded?

  • A Training job pauses temporarily
  • B Training job fails and stops
  • C Training job continues without impact
  • D Training job auto-saves and re-starts
Explanation Exceeding "MaxRuntimeInSeconds" results in the training job failing and stopping immediately.