Exam DSA-C03 Topic 1 Question 141 Discussion

Actual exam question for Snowflake's DSA-C03 exam
Question #: 141
Topic #: 1
You have a Snowflake Model Registry set up and are managing multiple versions of a machine learning model. You want to programmatically retrieve a specific version of the model and load it for inference within a Snowflake Snowpark Python UDE Assume your registry name is 'my_registry', the model name is 'credit risk_model', and you want to retrieve version 'v2'. How would you achieve this using Snowpark Python?

Suggested Answer: A Vote an answer

Option A correctly uses the method to directly load the model into memory for inference. This is the intended method for retrieving and using models managed by the Snowflake Model Registry. Option B uses 'joblib.load' which bypasses the Model Registry completely after getting the path. Option C is suitable if the model was trained using MLFlow, not generic scikit learn. Option D is an imaginary command not present in Model Registry and Option E involves calling udf to load and that is not right way to programatically load the model from registry and do inference with it.

by Kyle at Aug 03, 2025, 09:41 AM

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