Databricks-Machine-Learning-Professional Databricks Certified Machine Learning Professional Exam Practice Test

A machine learning engineer has created a webhook with the following code block:

Which of the following code blocks will trigger this webhook to run the associate job?

A)

B)

C)

D)

E)

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 data scientist has computed updated feature values for all primary key values stored in the Feature Store table features. In addition, feature values for some new primary key values have also been computed. The updated feature values are stored in the DataFrame features_df. They want to replace all data in features with the newly computed data.

Which of the following code blocks can they use to perform this task using the Feature Store Client fs?

A)

B)

C)

D)

E)

Which of the following is a probable response to identifying drift in a machine learning application?

Which of the following is a simple statistic to monitor for categorical feature drift?

A data scientist has developed and logged a scikit-learn random forest model model, and then they ended their Spark session and terminated their cluster. After starting a new cluster, they want to review the feature_importances_ of the original model object.

Which of the following lines of code can be used to restore the model object so that feature_importances_ is available?

A data scientist is utilizing MLflow to track their machine learning experiments. After completing a series of runs for the experiment with experiment ID exp_id, the data scientist wants to programmatically work with the experiment run data in a Spark DataFrame. They have an active MLflow Client client and an active Spark session spark.

Which of the following lines of code can be used to obtain run-level results for exp_id in a Spark DataFrame?