Databricks-Machine-Learning-Professional Exam Dumps

Get All Databricks Certified Machine Learning Professional Exam Questions with Validated Answers

Databricks-Machine-Learning-Professional Pack
Vendor: Databricks
Exam Code: Databricks-Machine-Learning-Professional
Exam Name: Databricks Certified Machine Learning Professional
Exam Questions: 60
Last Updated: May 21, 2026
Related Certifications: Machine Learning Professional
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Free Databricks Databricks-Machine-Learning-Professional Exam Actual Questions

Question No. 1

A machine learning engineer wants to deploy a model for real-time serving using MLflow Model Serving. For the model, the machine learning engineer currently has one model version in each of the stages in the MLflow Model Registry. The engineer wants to know which model versions can be queried once Model Serving is enabled for the model.

Which of the following lists all of the MLflow Model Registry stages whose model versions are automatically deployed with Model Serving?

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Correct Answer: D

Question No. 2

A data scientist is using MLflow to track their machine learning experiment. As a part of each MLflow run, they are performing hyperparameter tuning. The data scientist would like to have one parent run for the tuning process with a child run for each unique combination of hyperparameter values.

They are using the following code block:

The code block is not nesting the runs in MLflow as they expected.

Which of the following changes does the data scientist need to make to the above code block so that it successfully nests the child runs under the parent run in MLflow?

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Correct Answer: E

Question No. 3

Which of the following describes the purpose of the context parameter in the predict method of Python models for MLflow?

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Correct Answer: A

Question No. 4

Which of the following is a reason for using Jensen-Shannon (JS) distance over a Kolmogorov-Smirnov (KS) test for numeric feature drift detection?

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Correct Answer: D

Question No. 5

A machine learning engineer wants to log feature importance data from a CSV file at path importance_path with an MLflow run for model model.

Which of the following code blocks will accomplish this task inside of an existing MLflow run block?

A)

B)

C) mlflow.log_data(importance_path, "feature-importance.csv")

D) mlflow.log_artifact(importance_path, "feature-importance.csv")

E) None of these code blocks tan accomplish the task.

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Correct Answer: A

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