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As the lead Machine Learning Engineer at your company, you're tasked with developing ML models to digitize scanned customer forms. You've created a TensorFlow model that converts these scanned images into text and stores them in Cloud Storage. The company processes thousands of forms daily, and the solution must be cost-effective, scalable, and require minimal human intervention. Additionally, the solution must ensure data privacy and compliance with industry standards. Which of the following approaches best meets these requirements? (Choose one correct option)
A
Set up a serving pipeline in Compute Engine for predictions, ensuring auto-scaling is enabled to handle the load.
B
Deploy the model on AI Platform and create a version for online inference, using Cloud Scheduler to trigger predictions at scheduled intervals.
C
Leverage Cloud Functions to predict each time new data is added to Cloud Storage, ensuring immediate processing of each form.
D
Use AI Platform's batch prediction feature for automated processing, configuring it to automatically process new files added to Cloud Storage daily.