Databricks-Machine-Learning-Associate practice materials Questions Answers

Exam Code:
Databricks-Machine-Learning-Associate
Exam Name:
Databricks Certified Machine Learning Associate Exam
Last Update:
Jun 01,2026

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Page: 1 / 15
Total Questions: 74

Questions & Answers PDF

• Question 1

  

  A data scientist has produced two models for a single machine learning problem. One of the models performs well when one of the features has a value of less than 5, and the other model performs well when the value of that feature is greater than or equal to 5. The data scientist decides to combine the two models into a single machine learning solution.Which of the following terms is used to describe this combination of models?

  • Bootstrap aggregation
  • Support vector machines
  • Bucketing
  • Ensemble learning
  • Stacking

  Reveal Answer Answer: D Next Question

• Question 2

  

  A data scientist has written a data cleaning notebook that utilizes the pandas library, but their colleague has suggested that they refactor their notebook to scale with big data.Which of the following approaches can the data scientist take to spend the least amount of time refactoring their notebook to scale with big data?

  • They can refactor their notebook to process the data in parallel.
  • They can refactor their notebook to use the PySpark DataFrame API.
  • They can refactor their notebook to use the Scala Dataset API.
  • They can refactor their notebook to use Spark SQL.
  • They can refactor their notebook to utilize the pandas API on Spark.

  Reveal Answer Answer: E Next Question

• Question 3

  

  A data scientist has written a feature engineering notebook that utilizes the pandas library. As the size of the data processed by the notebook increases, the notebook's runtime is drastically increasing, but it is processing slowly as the size of the data included in the process increases.Which of the following tools can the data scientist use to spend the least amount of time refactoring their notebook to scale with big data?

  • PySpark DataFrame API
  • pandas API on Spark
  • Spark SQL
  • Feature Store

  Reveal Answer Answer: B Next Question

• Question 4

  

  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?

  • RMSE
  • Precision
  • Area under the residual operating curve
  • Accuracy
  • Recall

  Reveal Answer Answer: E Next Question

• Question 5

  

  A data scientist has been given an incomplete notebook from the data engineering team. The notebook uses a Spark DataFrame spark_df on which the data scientist needs to perform further feature engineering. Unfortunately, the data scientist has not yet learned the PySpark DataFrame API.Which of the following blocks of code can the data scientist run to be able to use the pandas API on Spark?

  • import pyspark.pandas as ps df = ps.DataFrame(spark_df)
  • import pyspark.pandas as ps df = ps.to_pandas(spark_df)
  • spark_df.to_sql()
  • import pandas as pddf = pd.DataFrame(spark_df)
  • spark_df.to_pandas()

  Reveal Answer Answer: A Next Question

• Question 6

  

  A data scientist has been given an incomplete notebook from the data engineering team. The notebook uses a Spark DataFrame spark_df on which the data scientist needs to perform further feature engineering. Unfortunately, the data scientist has not yet learned the PySpark DataFrame API.Which of the following blocks of code can the data scientist run to be able to use the pandas API on Spark?

  • import pyspark.pandas as ps df = ps.DataFrame(spark_df)
  • import pyspark.pandas as ps df = ps.to_pandas(spark_df)
  • spark_df.to_pandas()
  • import pandas as pd
  • df = pd.DataFrame(spark_df)

  Reveal Answer Answer: A Next Question

• Question 7

  

  A data scientist is using Spark SQL to import their data into a machine learning pipeline. Once the data is imported, the data scientist performs machine learning tasks using Spark ML.Which of the following compute tools is best suited for this use case?

  • Single Node cluster
  • Standard cluster
  • SQL Warehouse
  • None of these compute tools support this task

  Reveal Answer Answer: B Next Question

• Question 8

  

  Which of the following describes the relationship between native Spark DataFrames and pandas API on Spark DataFrames?

  • pandas API on Spark DataFrames are single-node versions of Spark DataFrames with additional metadata
  • pandas API on Spark DataFrames are more performant than Spark DataFrames
  • pandas API on Spark DataFrames are made up of Spark DataFrames and additional metadata
  • pandas API on Spark DataFrames are less mutable versions of Spark DataFrames
  • pandas API on Spark DataFrames are unrelated to Spark DataFrames

  Reveal Answer Answer: C Next Question

• Question 9

  

  Which of the following statements describes a Spark ML estimator?

  • An estimator is a hyperparameter arid that can be used to train a model
  • An estimator chains multiple alqorithms toqether to specify an ML workflow
  • An estimator is a trained ML model which turns a DataFrame with features into a DataFrame with predictions
  • An estimator is an alqorithm which can be fit on a DataFrame to produce a Transformer
  • An estimator is an evaluation tool to assess to the quality of a model

  Reveal Answer Answer: D Next Question

• Question 10

  

  A data scientist is developing a machine learning pipeline using AutoML on Databricks Machine Learning.Which of the following steps will the data scientist need to perform outside of their AutoML experiment?

  • Model tuning
  • Model evaluation
  • Model deployment
  • Exploratory data analysis

  Reveal Answer Answer: D Next Question

Page: 1 / 15
Total Questions: 74

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