Databricks-Machine-Learning-Professional Exam Dumps | A Machine Learning Engineer has created a custom PyFunc model wrapper for a fraud detection system that

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Question 26/96

A Machine Learning Engineer has created a custom PyFunc model wrapper for a fraud detection system that needs to be registered in Unity Catalog under the schema risk_models in the production catalog. The model requires specific dependencies and must be accessible for governance and version control. The engineer is working on a dedicated cluster with Unity Catalog enabled, but the model registration is failing. Why is the model failing to be registered in this case?

A. The model signature must be provided, as Unity Catalog requires all models to have signatures.

B. The cluster must be configured with shared access mode instead of dedicated mode.

C. The PyFunc model must inherit from mlflow.sklearn.Model instead of mlflow.pyfunc.PythonModel.

D. The model artifacts must be stored in DBFS rather than Unity Catalog volumes.

Question 26/96

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