Databricks Certified Machine Learning Professional Databricks Machine Learning Professional Exam Questions

A machine learning engineer needs to select a deployment strategy for a new machine learning application. The feature values are not available until the time of delivery, and results are needed exceedingly fast for one record at a time.

Which of the following deployment strategies can be used to meet these requirements?

A machine learning engineer has developed a random forest model using scikit-learn, logged the model using MLflow as random_forest_model, and stored its run ID in the run_id Python variable. They now want to deploy that model by performing batch inference on a Spark DataFrame spark_df.

Which of the following code blocks can they use to create a function called predict that they can use to complete the task?

A)

B)

It is not possible to deploy a scikit-learn model on a Spark DataFrame.

C)

D)

E)

A data scientist wants to remove the star_rating column from the Delta table at the location path. To do this, they need to load in data and drop the star_rating column.

Which of the following code blocks accomplishes this task?

A machine learning engineer wants to move their model version model_version for the MLflow Model Registry model model from the Staging stage to the Production stage using MLflow Client client.

Which of the following code blocks can they use to accomplish the task?

A)

B)

C)

D)

E)

A machine learning engineer is in the process of implementing a concept drift monitoring solution. They are planning to use the following steps:

1. Deploy a model to production and compute predicted values

2. Obtain the observed (actual) label values

3. _____

4. Run a statistical test to determine if there are changes over time

Which of the following should be completed as Step #3?

After a data scientist noticed that a column was missing from a production feature set stored as a Delta table, the machine learning engineering team has been tasked with determining when the column was dropped from the feature set.

Which of the following SQL commands can be used to accomplish this task?

A machine learning engineer is converting a Hyperopt-based hyperparameter tuning process from manual MLflow logging to MLflow Autologging. They are trying to determine how to manage nested Hyperopt runs with MLflow Autologging.

Which of the following approaches will create a single parent run for the process and a child run for each unique combination of hyperparameter values when using Hyperopt and MLflow Autologging?