Google Cloud

Google Cloud Certified – Professional Machine Learning Engineer

PR000269
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Validate your skills as a Professional Machine Learning Engineer with exam code PR000269 in Google Cloud.

495 questions 0 views Free
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Questions 21–30 of 495

Q21

You are configuring an AutoML model and encounter an error. What could primarily cause the model to not train?

  • A Insufficient training data
  • B High accuracy threshold
  • C Strong regularization settings
  • D Unverified Google account
Explanation Insufficient training data is the most common hindrance for model training, while other options are less likely causes.
Q22

Which service is best for training machine learning models at scale?

  • A Google Cloud AI Platform
  • B Google BigQuery
  • C Google Compute Engine
  • D Google Cloud Storage
Explanation Google Cloud AI Platform is designed for scaling ML models, while the others serve different functions.
Q23

A company needs to deploy a machine learning model with minimal downtime. What should they implement?

  • A Blue/Green deployment strategy
  • B Canary release only
  • C Rolling deployment with no monitoring
  • D Static IP address for the service
Explanation A Blue/Green deployment minimizes downtime by switching traffic smoothly, while others may introduce risks.
Q24

You are configuring AutoML for a text classification task. What happens if your dataset is highly imbalanced?

  • A Model performs optimally
  • B Increased risk of overfitting
  • C Bias towards the dominant class
  • D Only minority class predictions improve
Explanation Imbalanced datasets lead models to favor the dominant class, affecting overall accuracy.
Q25

Which Google Cloud service is primarily used for building machine learning models?

  • A Cloud AutoML
  • B Cloud Storage
  • C BigQuery
  • D Cloud Functions
Explanation Cloud AutoML is specifically designed for building ML models, while the others serve different functions.
Q26

A company needs to preprocess their data for a ML project. What would be the best service to use?

  • A BigQuery Data Transfer Service
  • B AI Platform Pipelines
  • C Dataproc
  • D Dataflow
Explanation Dataflow is ideal for real-time data preprocessing, while others focus on different aspects of data management or model deployment.
Q27

You are configuring a model for predictions using the AI Platform. What happens if the selected model is larger than the maximum deployment limit?

  • A Deployment will succeed with warnings.
  • B Deployment will fail with an error.
  • C The model will be downsized automatically.
  • D The model will be queued for resizing.
Explanation Model deployment fails if it exceeds the limit, while others suggest incorrect behaviors.
Q28

Which service should you use for real-time data processing?

  • A Cloud Dataflow
  • B Cloud Storage
  • C Cloud Pub/Sub
  • D BigQuery
Explanation Cloud Dataflow is designed for real-time data processing; the others do not provide real-time capabilities.
Q29

A company needs to build a machine learning model to predict customer churn using historical transaction data. What metric should primarily guide model evaluation?

  • A Accuracy
  • B F1 Score
  • C AUC-ROC
  • D Mean Squared Error
Explanation AUC-ROC is crucial for classification tasks like churn prediction to measure trade-offs between true and false positives; accuracy may mislead in imbalanced datasets.
Q30

You are configuring a Google Cloud AI Platform model version for deployment. What happens when you set the traffic allocation to zero?

  • A The model becomes inactive
  • B Traffic is directed to another version
  • C No predictions can be made
  • D The model is deleted
Explanation Setting traffic allocation to zero directs traffic to other active model versions, maintaining service availability; the model remains deployed.