Professional-Machine-Learning-Engineer Exam Dumps | You are working on a system log anomaly detection model for a cybersecurity organization. You have developed

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Question 39/52

You are working on a system log anomaly detection model for a cybersecurity organization. You have developed the model using TensorFlow, and you plan to use it for real-time prediction. You need to create a Dataflow pipeline to ingest data via Pub/Sub and write the results to BigQuery. You want to minimize the serving latency as much as possible. What should you do?

A. Deploy the model to a Vertex AI endpoint, and invoke this endpoint in the Dataflow job.

B. Load the model directly into the Dataflow job as a dependency, and use it for prediction.

C. Deploy the model in a TFServing container on Google Kubernetes Engine, and invoke it in the Dataflow job.

D. Containerize the model prediction logic in Cloud Run, which is invoked by Dataflow.

Question 39/52

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