Question 77 of 280
Single answerYou need to execute a batch prediction on 100 million records in a BigQuery table with a custom TensorFlow DNN
regressor model, and then store the predicted results in a BigQuery table. You want to minimize the effort required
to build this inference pipeline. What should you do?
✓AImport the TensorFlow model with BigQuery ML, and run the ml.predict function.
BUse the TensorFlow BigQuery reader to load the data, and use the BigQuery API to write the results to
BigQuery.
CCreate a Dataflow pipeline to convert the data in BigQuery to TFRecords. Run a batch inference on Vertex AI
Prediction, and write the results to BigQuery.
DLoad the TensorFlow SavedModel in a Dataflow pipeline. Use the BigQuery I/O connector with a custom
function to perform the inference within the pipeline, and write the results to BigQuery.
✓
Correct Answer: A
Import the TensorFlow model with BigQuery ML, and run the ml.predict function.
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Explanation
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