You work as a machine learning specialist for a data mining department of a large bank. Your department is responsible for leveraging the bank`s huge data lake to gain insights and make predictions for your marketing and risk departments. Your team’s latest project, an XGBoost prediction model, is ready for production deployment. However, you want to run some additional batch predictions using a batch inference job to make sure your model can handle the production prediction workload. In your SageMaker notebook, how do you extend your estimator to read input data in batch from a specified S3 bucket and make predictions?

Answer options:

A.Extend the estimator to a Transformer object.
B.Extend the estimator to a Predictor object.
C.Extend the estimator to a MultiDataModel object.
D.Extend the estimator to a BatchPredictor object.

Correct Answer: A
Option A is correct. You can extend your estimator to a transformer object, which is derived from the SageMaker Transformer class. The batch transformer reads input data from a specified S3 bucket and makes predictions.
Option B is incorrect. The Predictor object makes prediction requests to an Amazon SageMaker endpoint. However, it is not the SageMaker API used to perform batch predictions.
Option C is incorrect. The MultiDataModel object is used to deploy multiple models to the same endpoint, not to make batch predictions.
Option D is incorrect. There is no BatchPredictor SageMaker API.
References:
Please see the Amazon SageMaker developer guide titled Deploy a Model in Amazon SageMaker (https://docs.aws.amazon.com/sagemaker/latest/dg/how-it-works-deployment.html),
The Amazon SageMaker developer guide titled Step 5: Deploy the Model to Amazon EC2 (https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-model-deployment.html#ex1-deploy-model), a
The SageMaker API page titled Transformer (https://sagemaker.readthedocs.io/en/stable/api/inference/transformer.html),
The SageMaker API page titled Predictors (https://sagemaker.readthedocs.io/en/stable/api/inference/predictors.html),
The SageMaker API page titled MultiDataModel (https://sagemaker.readthedocs.io/en/stable/api/inference/multi_data_model.html),
The SageMaker API page titled Inference APIs (https://sagemaker.readthedocs.io/en/stable/api/inference/index.html)