Use the Snowflake Model Registry SNOWPRO-ADVANCED-DATA-SCIENTIST Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   What is the output of a model's predict() method in Snowflake?

   • AA Snowpark DataFrame containing the predictions
   • BA SQL query string
   • CA Python list of predictions
   • DA JSON object
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2. 7foundation · easy

   When registering a model, which of the following is required as metadata?

   • AThe model's training data
   • BA model name and version
   • CThe model's hyperparameters
   • DThe training script
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4. 8application · medium

   A company wants to standardize how machine learning models are managed across different teams. They currently have models stored in various locations, including local files and external systems. They want to use the Snowflake Model Registry to centralize model management. What is the first step they should take?

   • ARegister all existing models into the Snowflake Model Registry with appropriate metadata.
   • BCreate a new database and schema for the model registry.
   • CSet up a separate external model registry and sync it with Snowflake.
   • DTrain new models using Snowpark ML to ensure compatibility.
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5. 9foundation · easy

   In Snowflake, which Python API is used to register a trained model into the Model Registry?

   • Asnowflake.ml.registry
   • Bsnowflake.connector
   • Csnowflake.snowpark
   • Dsnowflake.ml.modeling
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6. 10foundation · easy

   How does the Snowflake Model Registry handle multiple versions of the same model?

   • AIt merges versions into a single ensemble model
   • BIt keeps only the latest version and deletes older ones automatically
   • CIt requires a different model name for each version
   • DIt stores them as separate entries with the same model name but different version identifiers
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