DATABRICKS-MACHINE-LEARNING-PROFESSIONAL Online Practice Questions and Answers

A data scientist has developed a model to predict ice cream sales using the expected temperature and expected number of hours of sun in the day. However, the expected temperature is dropping beneath the range of the input variable on

which the model was trained.

Which of the following types of drift is present in the above scenario?

A. Label drift

B. None of these

C. Concept drift

D. Prediction drift

E. Feature drift

A data scientist has developed a model model and computed the RMSE of the model on the test set. They have assigned this value to the variable rmse. They now want to manually store the RMSE value with the MLflow run.

They write the following incomplete code block:

image9

Which of the following lines of code can be used to fill in the blank so the code block can successfully complete the task?

A. log_artifact

B. log_model

C. log_metric

D. log_param

E. There is no way to store values like this.

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?

A. Staging, Production, Archived

B. Production

C. None, Staging, Production, Archived

D. Staging, Production

E. None, Staging, Production

A data scientist has developed a scikit-learn model sklearn_model and they want to log the model using MLflow.

They write the following incomplete code block:

image14

Which of the following lines of code can be used to fill in the blank so the code block can successfully complete the task?

A. mlflow.spark.track_model(sklearn_model, "model")

B. mlflow.sklearn.log_model(sklearn_model, "model")

C. mlflow.spark.log_model(sklearn_model, "model")

D. mlflow.sklearn.load_model("model")

E. mlflow.sklearn.track_model(sklearn_model, "model")

Which of the following describes the concept of MLflow Model flavors?

A. A convention that deployment tools can use to wrap preprocessing logic into a Model

B. A convention that MLflow Model Registry can use to version models

C. A convention that MLflow Experiments can use to organize their Runs by project

D. A convention that deployment tools can use to understand the model

E. A convention that MLflow Model Registry can use to organize its Models by project

A machine learning engineer has developed a model and registered it using the FeatureStoreClient fs. The model has model URI model_uri. The engineer now needs to perform batch inference on customer-level Spark DataFrame spark_df,

but it is missing a few of the static features that were used when training the model. The customer_id column is the primary key of spark_df and the training set used when training and logging the model.

Which of the following code blocks can be used to compute predictions for spark_df when the missing feature values can be found in the Feature Store by searching for features by customer_id?

A. df = fs.get_missing_features(spark_df, model_uri) fs.score_model(model_uri, df)

B. fs.score_model(model_uri, spark_df)

C. df = fs.get_missing_features(spark_df, model_uri) fs.score_batch(model_uri, df)

D. df = fs.get_missing_features(spark_df) fs.score_batch(model_uri, df)

E. fs.score_batch(model_uri, spark_df)

A machine learning engineer wants to programmatically create a new Databricks Job whose schedule depends on the result of some automated tests in a machine learning pipeline. Which of the following Databricks tools can be used to programmatically create the Job?

A. MLflow APIs

B. AutoML APIs

C. MLflow Client

D. Jobs cannot be created programmatically

E. Databricks REST APIs

A data scientist has created a Python function compute_features that returns a Spark DataFrame with the following schema

The resulting DataFrame is assigned to the features_df variable. The data scientist wants to create a Feature Store table using features_df. Which of the following code blocks can they use to create and populate the Feature Store table using the Feature Store Client fs?

A. Option A

B. Option B

C. Option C

D. Option D

E. Option E

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. Option A

B. Option B

C. Option C

D. Option D

E. Option E

A machine learning engineer is attempting to create a webhook that will trigger a Databricks Job job_id when a model version for model model transitions into any MLflow Model Registry stage. They have the following incomplete code block:

Which of the following lines of code can be used to fill in the blank so that the code block accomplishes the task?

A. "MODEL_VERSION_CREATED"

B. "MODEL_VERSION_TRANSITIONED_TO_PRODUCTION"

C. "MODEL_VERSION_TRANSITIONED_TO_STAGING"

D. "MODEL_VERSION_TRANSITIONED_STAGE"

E. "MODEL_VERSION_TRANSITIONED_TO_STAGING", "MODEL_VERSION_TRANSITIONED_TO_PRODUCTION"