Databricks Machine Learning Professional Exam Questions Instant Access

Question 1

A machine learning engineer has registered a sklearn model in the MLflow Model Registry using the sklearn model flavor with UI model_uri.

Which of the following operations can be used to load the model as an sklearn object for batch deployment?

Amlflow.spark.load_model(model_uri)

Bmlflow.pyfunc.read_model(model_uri)

Cmlflow.sklearn.read_model(model_uri)

Dmlflow.pyfunc.load_model(model_uri)

Emlflow.sklearn.load_model(model_uri)

Answer : D

Question 2

A machine learning engineer wants to view all of the active MLflow Model Registry Webhooks for a specific model.

They are using the following code block:

Which of the following changes does the machine learning engineer need to make to this code block so it will successfully accomplish the task?

AThere are no necessary changes

BReplace list with view in the endpoint URL

CReplace POST with GET in the call to http request

DReplace list with webhooks in the endpoint URL

EReplace POST with PUT in the call to http request

Answer : D

Question 3

A machine learning engineer and data scientist are working together to convert a batch deployment to an always-on streaming deployment. The machine learning engineer has expressed that rigorous data tests must be put in place as a part of their conversion to account for potential changes in data formats.

Which of the following describes why these types of data type tests and checks are particularly important for streaming deployments?

ABecause the streaming deployment is always on, all types of data must be handled without producing an error

BAll of these statements

CBecause the streaming deployment is always on, there is no practitioner to debug poor model performance

DBecause the streaming deployment is always on, there is a need to confirm that the deployment can autoscale

ENone of these statements

Answer : D

Question 4

A data scientist set up a machine learning pipeline to automatically log a data visualization with each run. They now want to view the visualizations in Databricks.

Which of the following locations in Databricks will show these data visualizations?

AThe MLflow Model Registry Model paqe

BThe Artifacts section of the MLflow Experiment page

CLogged data visualizations cannot be viewed in Databricks

DThe Artifacts section of the MLflow Run page

EThe Figures section of the MLflow Run page

Answer : E

Question 5

Which of the following is an advantage of using the python_function(pyfunc) model flavor over the built-in library-specific model flavors?

Apython_function provides no benefits over the built-in library-specific model flavors

Bpython_function can be used to deploy models in a parallelizable fashion

Cpython_function can be used to deploy models without worrying about which library was used to create the model

Dpython_function can be used to store models in an MLmodel file

Epython_function can be used to deploy models without worrying about whether they are deployed in batch, streaming, or real-time environments

Answer : B

Question 6

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?

Aspark.read.format(''delta'').load(path).drop(''star_rating'')

Bspark.read.format(''delta'').table(path).drop(''star_rating'')

CDelta tables cannot be modified

Dspark.read.table(path).drop(''star_rating'')

Espark.sql(''SELECT * EXCEPT star_rating FROM path'')

Answer : D

Question 7

Which of the following is a benefit of logging a model signature with an MLflow model?

AThe model will have a unique identifier in the MLflow experiment

BThe schema of input data can be validated when serving models

CThe model can be deployed using real-time serving tools

DThe model will be secured by the user that developed it

EThe schema of input data will be converted to match the signature

Answer : E

Databricks Certified Machine Learning Professional Databricks Machine Learning Professional Exam Questions