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  • Exam Name: Databricks Certified Machine Learning Associate Exam
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Databricks-Machine-Learning-Associate Questions and Answers

Question # 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

Question # 2

A data scientist has developed a linear regression model using Spark ML and computed the predictions in a Spark DataFrame preds_df with the following schema:

prediction DOUBLE

actual DOUBLE

Which of the following code blocks can be used to compute the root mean-squared-error of the model according to the data in preds_df and assign it to the rmse variable?

A)

Databricks-Machine-Learning-Associate question answer

B)

Databricks-Machine-Learning-Associate question answer

C)

Databricks-Machine-Learning-Associate question answer

D)

Databricks-Machine-Learning-Associate question answer

E)

Databricks-Machine-Learning-Associate question answer

A.

Option A

B.

Option B

C.

Option C

D.

Option D

E.

Option E

Question # 3

Which of the following statements describes a Spark ML estimator?

A.

An estimator is a hyperparameter arid that can be used to train a model

B.

An estimator chains multiple alqorithms toqether to specify an ML workflow

C.

An estimator is a trained ML model which turns a DataFrame with features into a DataFrame with predictions

D.

An estimator is an alqorithm which can be fit on a DataFrame to produce a Transformer

E.

An estimator is an evaluation tool to assess to the quality of a model

Question # 4

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

A.

pandas API on Spark DataFrames are single-node versions of Spark DataFrames with additional metadata

B.

pandas API on Spark DataFrames are more performant than Spark DataFrames

C.

pandas API on Spark DataFrames are made up of Spark DataFrames and additional metadata

D.

pandas API on Spark DataFrames are less mutable versions of Spark DataFrames

E.

pandas API on Spark DataFrames are unrelated to Spark DataFrames

Question # 5

Which of the following tools can be used to distribute large-scale feature engineering without the use of a UDF or pandas Function API for machine learning pipelines?

A.

Keras

B.

Scikit-learn

C.

PyTorch

D.

Spark ML

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