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Q11 Single choice

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?

A
Use the Apache Airflow SDK to create multiple operators that use Dataflow and Vertex AI services.
Deploy the workflow on Cloud Composer.
B
Use the MLFlow SDK and deploy it on a Google Kubernetes Engine cluster. Create multiple
components that use Dataflow and Vertex AI services.
C
Use the Kubeflow Pipelines (KFP) SDK to create multiple components that use Dataflow and Vertex AI
services. Deploy the workflow on Vertex AI Pipelines.
D
Use the TensorFlow Extended (TFX) SDK to create multiple components that use Dataflow and Vertex
AI services. Deploy the workflow on Vertex AI Pipelines.

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