Databricks Certified Machine Learning Professional: DATABRICKS-MACHINE-LEARNING-PROFESSIONAL

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. spark.read.format(“delta”).load(path).drop(“star_rating”)

B. spark.read.format(“delta”).table(path).drop(“star_rating”)

C. Delta tables cannot be modified

D. spark.read.table(path).drop(“star_rating”)

E. spark.sql(“SELECT * EXCEPT star_rating FROM path”)

A data scientist has developed a scikit-learn random forest model model, but they have not yet logged model with MLflow. They want to obtain the input schema and the output schema of the model so they can document what type of data is

expected as input.

Which of the following MLflow operations can be used to perform this task?

A. mlflow.models.schema.infer_schema

B. mlflow.models.signature.infer_signature

C. mlflow.models.Model.get_input_schema

D. mlflow.models.Model.signature

E. There is no way to obtain the input schema and the output schema of an unlogged model.

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. Option A

B. Option B

C. Option C

D. Option D

E. Option E