Exam Professional-Machine-Learning-Engineer Topic 3 Question 156 Discussion

Actual exam question for Google's Professional-Machine-Learning-Engineer exam
Question #: 156
Topic #: 3

You have recently trained a scikit-learn model that you plan to deploy on Vertex Al. This model will support both online and batch prediction. You need to preprocess input data for model inference. You want to package the model for deployment while minimizing additional code What should you do?

A. 1 Upload your model to the Vertex Al Model Registry by using a prebuilt scikit-learn prediction container
2 Deploy your model to Vertex Al Endpoints, and create a Vertex Al batch prediction job that uses the instanceConfig.inscanceType setting to transform your input data B. 1. Create a custom container for your sci-kit learn model,
2 Define a custom serving function for your model
3 Upload your model and custom container to Vertex Al Model Registry
4 Deploy your model to Vertex Al Endpoints, and create a Vertex Al batch prediction job C. 1 Wrap your model in a custom prediction routine (CPR). and build a container image from the CPR local model
2 Upload your sci-kit learn model container to Vertex Al Model Registry
3 Deploy your model to Vertex Al Endpoints, and create a Vertex Al batch prediction job D. 1 Create a custom container for your sci-kit learn model.
2 Upload your model and custom container to Vertex Al Model Registry
3 Deploy your model to Vertex Al Endpoints, and create a Vertex Al batch prediction job that uses the instanceConfig. instanceType setting to transform your input data

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