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 41–50 of 495

Q41

You are configuring a machine learning model for a client. They require a high degree of interpretability. What should you use?

  • A Ensemble methods
  • B Deep Neural Networks
  • C Linear Regression
  • D Gradient Boosting
Explanation Linear Regression is inherently interpretable, while others are more complex.
Q42

What happens when an ML model is trained with biased data?

  • A Model accuracy increases
  • B Results are more generalized
  • C Performance is unchanged
  • D Model predictions may be unfair
Explanation Biased data typically leads to unfair predictions, affecting model integrity.
Q43

Which Google Cloud service provides fully managed data warehousing?

  • A BigQuery
  • B Cloud Storage
  • C Cloud Spanner
  • D Cloud SQL
Explanation BigQuery is designed for data warehousing, while others serve different purposes.
Q44

A company needs to deploy a machine learning model with low latency for real-time predictions. Which Google Cloud service should they use?

  • A Cloud ML Engine
  • B Cloud Functions
  • C AI Platform Prediction
  • D Dataflow
Explanation AI Platform Prediction is specifically designed for real-time predictions, unlike the others, which have different uses.
Q45

You are configuring a Continuous Integration/Continuous Deployment (CI/CD) pipeline. What should you use to manage connections to Cloud services securely within the pipeline?

  • A Service Account
  • B API Key
  • C Environment Variables
  • D IAM Policies
Explanation Service Accounts manage secure access, while the others lack the appropriate security context for CI/CD.
Q46

Which service allows for seamless serverless machine learning model deployment?

  • A AI Platform Predictions
  • B Compute Engine
  • C Cloud Functions
  • D App Engine
Explanation AI Platform Predictions is specifically designed for ML model deployment, while others serve different purposes.
Q47

A company needs to analyze large streams of data in real-time. Which Google Cloud service should they choose?

  • A BigQuery
  • B Cloud Pub/Sub
  • C Cloud Storage
  • D Cloud Dataflow
Explanation Cloud Pub/Sub is optimized for ingesting data in real-time, while others focus on batch processing or data storage.
Q48

What happens when you set a model's learning rate too high during training?

  • A Increased accuracy until convergence
  • B Oscillating loss during training
  • C Faster convergence guaranteed
  • D Overfitting of model occurs
Explanation A high learning rate can cause oscillations in the loss, leading to poor model performance, while the other options suggest unrealistic outcomes.
Q49

Which service is best for scalable machine learning model deployment?

  • A AI Platform
  • B Cloud Functions
  • C Cloud Run
  • D Google Kubernetes Engine
Explanation AI Platform is specifically designed for scalable machine learning deployments; the others serve different purposes.
Q50

A company needs to analyze streaming data in real-time. Which Google Cloud service should they use?

  • A BigQuery
  • B Dataflow
  • C Cloud Storage
  • D Pub/Sub
Explanation Dataflow is optimized for real-time stream processing, while the others are more suited for batch or static data analysis.