PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #303
PROFESSIONAL-MACHINE-LEARNING-ENGINEER Question #303: Real Exam Question with Answer & Explanation
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Question
You are developing a TensorFlow Extended (TFX) pipeline with standard TFX components. The pipeline includes data preprocessing steps. After the pipeline is deployed to production, it will process up to 100 TB of data stored in BigQuery. You need the data preprocessing steps to scale efficiently, publish metrics and parameters to Vertex AI Experiments, and track artifacts by using Vertex ML Metadata. How should you configure the pipeline run?
Options
- ARun the TFX pipeline in Vertex AI Pipelines. Configure the pipeline to use Vertex AI Training jobs
- BRun the TFX pipeline in Vertex AI Pipelines. Set the appropriate Apache Beam parameters in the
- CRun the TFX pipeline in Dataproc by using the Apache Beam TFX orchestrator. Set the
- DRun the TFX pipeline in Dataflow by using the Apache Beam TFX orchestrator. Set the appropriate
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