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 201–210 of 486

Q201

You are configuring a machine learning model using multiple input features. What happens if you include a feature with significantly higher variance than others?

  • A Model performance improves
  • B Feature normalization is unnecessary
  • C It may dominate other features
  • D Only affects training time
Explanation A feature with higher variance can dominate model training, potentially leading to worse generalization, while the other choices are misleading.
Q202

Which AWS service is designed specifically for building and training machine learning models?

  • A Amazon SageMaker
  • B AWS Lambda
  • C AWS CodePipeline
  • D Amazon RDS
Explanation Amazon SageMaker is purpose-built for machine learning; the others serve different functions.
Q203

A company needs to deploy a machine learning model with automatic scaling. Which AWS service should they use?

  • A AWS Elastic Beanstalk
  • B AWS EC2
  • C AWS Fargate
  • D AWS Glue
Explanation AWS Fargate provides automatic scaling for containerized applications; the other options do not have this feature.
Q204

What happens when you enable data versioning on an AWS S3 bucket?

  • A Delete old versions permanently
  • B Track every object version
  • C Compress objects automatically
  • D Encrypt all data automatically
Explanation Data versioning allows tracking of every object version; the other options do not pertain to versioning.
Q205

Which service is best suited for real-time data analytics on streaming data?

  • A Amazon Kinesis
  • B Amazon S3
  • C Amazon RDS
  • D Amazon Athena
Explanation Amazon Kinesis specializes in real-time data processing, while the others are for storage and querying.
Q206

A company needs to improve their machine learning model accuracy. Which approach is NOT recommended?

  • A Collect more diverse training data
  • B Use regularization techniques
  • C Increase model complexity without limits
  • D Conduct hyperparameter tuning
Explanation Increased model complexity can lead to overfitting, unlike the other approaches which aim to improve generalization.
Q207

What happens when an IAM policy explicitly denies access?

  • A Access is always granted
  • B Access is denied regardless of permissions
  • C Access is allowed if explicitly permitted
  • D Access is denied only for specific resources
Explanation An explicit deny in IAM policies overrides any allow permissions, ensuring access is denied.
Q208

A data scientist wants to deploy a TensorFlow model using serverless architecture. Which AWS service is most suitable?

  • A AWS Lambda
  • B Amazon EC2
  • C Amazon SageMaker
  • D AWS Batch
Explanation Amazon SageMaker provides managed services for deploying ML models efficiently.
Q209

What is a key benefit of using Amazon Rekognition for image analysis?

  • A Custom model training
  • B Live streaming video processing
  • C Automatic scaling management
  • D Facial recognition and analysis
Explanation Amazon Rekognition specializes in facial recognition and image analysis tasks.
Q210

You are configuring a batch transform job in Amazon SageMaker. What happens if you forget to specify the S3 output path?

  • A Job will fail immediately
  • B Default path is used
  • C No results will be saved
  • D Output will be logged to CloudWatch
Explanation If an output path is not provided, results will not be saved in S3.