Amazon SageMaker Autopilot model deployment and prediction
This Amazon SageMaker Autopilot guide includes steps for model deployment, setting up real-time inference, and running inference with batch jobs.
After you train your SageMaker Autopilot models, you can deploy them to get predictions in one of two ways:
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Use Real-time inferencing to set up an endpoint and obtain predictions interactively.
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Use Batch inferencing to make predictions in parallel on batches of observations on an entire dataset.
To avoid incurring unnecessary charges: After the endpoints and resources that were
created from model deployment are longer needed, you can delete them. For information about
pricing of instances by Region, see Amazon SageMaker Pricing