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 11–20 of 495

Q11

A company needs to run a large-scale deep learning model. Which Google Cloud service should they use?

  • A Cloud Functions
  • B Compute Engine
  • C App Engine
  • D Cloud Run
Explanation Compute Engine offers virtual machines suitable for resource-intensive tasks like deep learning, while others are more suited for lightweight applications.
Q12

What happens when you increase the dropout rate in a neural network?

  • A Model accuracy decreases
  • B Model overfitting increases
  • C Training time decreases
  • D Model generalization improves
Explanation Increasing the dropout rate enhances generalization by preventing overfitting, countering the other options' claims.
Q13

Which service allows real-time data analytics in Google Cloud?

  • A BigQuery
  • B Cloud Pub/Sub
  • C Cloud Functions
  • D Cloud Run
Explanation Cloud Pub/Sub enables real-time messaging and event-driven architectures, making it suitable for real-time analytics, while BigQuery is primarily for big data processing in batch mode.
Q14

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

  • A AI Platform
  • B Cloud Functions
  • C BigQuery ML
  • D Vertex AI
Explanation Vertex AI is optimized for serving ML models in real-time with low latency, while the other options either focus on batch processing or do not specialize in low-latency predictions.
Q15

What happens when you train a model on a dataset that is highly imbalanced?

  • A Increased accuracy for the minority class
  • B Model overfits to the majority class
  • C Better performance overall
  • D Fast convergence during training
Explanation A highly imbalanced dataset often leads to models that favor the majority class, resulting in poor generalization and performance on the minority class.
Q16

Which service is designed for large-scale data processing in Google Cloud?

  • A BigQuery
  • B Cloud Datastore
  • C Cloud Functions
  • D Cloud Storage
Explanation BigQuery is optimized for analytics and processing large datasets, while others serve different purposes.
Q17

A company needs to analyze their customer data with real-time machine learning. Which Google Cloud service should they use?

  • A AI Platform
  • B Cloud SQL
  • C Pub/Sub
  • D Dataflow
Explanation Dataflow allows for real-time processing pipelines for machine learning applications.
Q18

You are configuring a model that uses a large dataset with many features. What should you consider?

  • A Eliminate all unused features.
  • B Use dimensionality reduction techniques.
  • C Increase the size of your model.
  • D Assume all features are equally important.
Explanation Dimensionality reduction techniques improve model performance and reduce complexity by eliminating redundancies.
Q19

Which service would you use for real-time data analytics on streaming data?

  • A BigQuery
  • B Cloud Pub/Sub
  • C Dataflow
  • D Cloud Functions
Explanation Dataflow is designed for real-time processing, while other options serve different purposes.
Q20

A company needs to store large amounts of unstructured data. Which option is preferable?

  • A Cloud SQL
  • B Cloud Storage
  • C BigQuery
  • D Firestore
Explanation Cloud Storage is optimized for unstructured data, unlike the other options which have specific formats or structures.