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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #224

PROFESSIONAL-MACHINE-LEARNING-ENGINEER Question #224: Real Exam Question with Answer & Explanation

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Submitted by tarun92· Apr 18, 2026ML pipeline operationalization

Question

You are building a TensorFlow text-to-image generative model by using a dataset that contains billions of images with their respective captions. You want to create a low maintenance, automated workflow that reads the data from a Cloud Storage bucket collects statistics, splits the dataset into training/validation/test datasets performs data transformations trains the model using the training/validation datasets, and validates the model by using the test dataset. What should you do?

Options

  • AUse the Apache Airflow SDK to create multiple operators that use Dataflow and Vertex AI
  • BUse the MLFlow SDK and deploy it on a Google Kubernetes Engine cluster. Create multiple
  • CUse the Kubeflow Pipelines (KFP) SDK to create multiple components that use Dataflow and
  • DUse the TensorFlow Extended (TFX) SDK to create multiple components that use Dataflow and

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Topics

#MLOps#Data Pipelines#TensorFlow Extended (TFX)#Workflow Orchestration
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