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Databricks Certified Machine Learning Associate Exam Actual Questions

The questions for Certified Machine Learning Associate were last updated on Oct. 16, 2024.
  • Viewing page 1 out of 19 pages.
  • Viewing questions 1-4 out of 74 questions

Topic 1 - Exam A

Question #1 Topic 1

A machine learning engineer has created a Feature Table new_table using Feature Store Client fs. When creating the table, they specified a metadata description with key information about the Feature Table. They now want to retrieve that metadata programmatically.
Which of the following lines of code will return the metadata description?

  • A. There is no way to return the metadata description programmatically.
  • B. fs.create_training_set("new_table")
  • C. fs.get_table("new_table").description
  • D. fs.get_table("new_table").load_df()
  • E. fs.get_table("new_table")
Reveal Solution Hide Solution   Discussion   1

Correct Answer: C 🗳️

Question #2 Topic 1

A data scientist has a Spark DataFrame spark_df. They want to create a new Spark DataFrame that contains only the rows from spark_df where the value in column price is greater than 0.
Which of the following code blocks will accomplish this task?

  • A. spark_df[spark_df["price"] > 0]
  • B. spark_df.filter(col("price") > 0)
  • C. SELECT * FROM spark_df WHERE price > 0
  • D. spark_df.loc[spark_df["price"] > 0,:]
  • E. spark_df.loc[:,spark_df["price"] > 0]
Reveal Solution Hide Solution   Discussion   3

Correct Answer: B 🗳️

Question #3 Topic 1

A health organization is developing a classification model to determine whether or not a patient currently has a specific type of infection. The organization's leaders want to maximize the number of positive cases identified by the model.
Which of the following classification metrics should be used to evaluate the model?

  • A. RMSE
  • B. Precision
  • C. Area under the residual operating curve
  • D. Accuracy
  • E. Recall
Reveal Solution Hide Solution   Discussion   1

Correct Answer: E 🗳️

Question #4 Topic 1

In which of the following situations is it preferable to impute missing feature values with their median value over the mean value?

  • A. When the features are of the categorical type
  • B. When the features are of the boolean type
  • C. When the features contain a lot of extreme outliers
  • D. When the features contain no outliers
  • E. When the features contain no missing values
Reveal Solution Hide Solution   Discussion   1

Correct Answer: C 🗳️

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