What should you do?

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.

View Answer

Answer: D

Explanation:

This answer is correct because it allows you to use the trained TensorFlow model for batch predictions on text data stored in BigQuery without any additional processing or overhead. Al Platform provides a service for running batch prediction jobs that can take input data from BigQuery or Cloud Storage and write the output to BigQuery or Cloud Storage. You can use the SavedModel format to export your TensorFlow model to Cloud Storage and then submit a batch prediction job that points to the model location and the input data location. Al Platform will handle the scaling and distribution of the prediction requests and return the results in the specified output location.

Reference: [Al Platform: Batch prediction overview]

[Al Platform: Exporting a SavedModel for prediction]