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Home Databricks Certified Machine Learning Professional

Databricks Certified Machine Learning Professional Exam Practice Questions (P. 4)

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Question #16
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?
  1. A
    VERSION
  2. B
    DESCRIBE
  3. C
    HISTORY
  4. D
    DESCRIBE HISTORY
  5. E
    TIMESTAMP

Correct Answer:
D
chatbot-img GPT-4o - Answer
The DESCRIBE HISTORY command is ideal for investigating changes in Delta tables, including when columns were added or removed. By examining the chronological alterations stored, the team can pinpoint exactly when modifications occurred, making it possible to trace back to the specific event of the column's deletion. This SQL command provides comprehensive information about the sequence and nature of changes applied to the Delta table, making it a critical tool for diagnostics in data management and integrity verification.

Question #17
Which of the following describes label drift?
  1. A
    Label drift is when there is a change in the distribution of the predicted target given by the model
  2. B
    None of these describe label drift
  3. C
    Label drift is when there is a change in the distribution of an input variable
  4. D
    Label drift is when there is a change in the relationship between input variables and target variables
  5. E
    Label drift is when there is a change in the distribution of a target variable

Correct Answer:
C

Question #18
Which of the following machine learning model deployment paradigms is the most common for machine learning projects?
  1. A
    On-device
  2. B
    Streaming
  3. C
    Real-time
  4. D
    Batch
  5. E
    None of these deployments

Correct Answer:
B

Question #19
A data scientist would like to enable MLflow Autologging for all machine learning libraries used in a notebook. They want to ensure that MLflow Autologging is used no matter what version of the Databricks Runtime for Machine Learning is used to run the notebook and no matter what workspace-wide configurations are selected in the Admin Console.
Which of the following lines of code can they use to accomplish this task?
  1. A
    mlflow.sklearn.autolog()
  2. B
    mlflow.spark.autolog()
  3. C
    spark.conf.set(“autologging”, True)
  4. D
    It is not possible to automatically log MLflow runs.
  5. E
    mlflow.autolog()

Correct Answer:
C

Question #20
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:

Which of the following lines of code can be used to fill in the blank so the code block can successfully complete the task?
  1. A
    log_artifact
  2. B
    log_model
  3. C
    log_metric
  4. D
    log_param
  5. E
    There is no way to store values like this.

Correct Answer:
A

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