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1.You have trained a text classification model in TensorFlow using Al Platform. You want to use the trained
model for batch predictions on text data stored in BigQuery while minimizing computational overhead.
What should you do?
A. Export the model to BigQuery ML.
B. Deploy and version the model on Al Platform.
C. Use Dataflow with the SavedModel to read the data from BigQuery
D. Submit a batch prediction job on Al Platform that points to the model location in Cloud Storage.
2.You built and manage a production system that is responsible for predicting sales numbers. Model
accuracy is crucial, because the production model is required to keep up with market changes. Since being
deployed to production, the model hasn't changed; however the accuracy of the model has steadily
What issue is most likely causing the steady decline in model accuracy?
A. Poor data quality
B. Lack of model retraining
C. Too few layers in the model for capturing information
D. Incorrect data split ratio during model training, evaluation, validation, and test
3.You have written unit tests for a Kubeflow Pipeline that require custom libraries. You want to automate
the execution of unit tests with each new push to your development branch in Cloud Source Repositories.
What should you do?
A. Write a script that sequentially performs the push to your development branch and executes the unit
tests on Cloud Run
B. Using Cloud Build, set an automated trigger to execute the unit tests when changes are pushed to your
C. Set up a Cloud Logging sink to a Pub/Sub topic that captures interactions with Cloud Source
Repositories Configure a Pub/Sub trigger for Cloud Run, and execute the unit tests
on Cloud Run.
D. Set up a Cloud Logging sink to a Pub/Sub topic that captures interactions with Cloud Source
Repositories. Execute the unit tests using a Cloud Function that is triggered when messages are sent to
the Pub/Sub topic