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Databricks Databricks-Machine-Learning-Associate Exam With Confidence Using Practice Dumps

Exam Code:
Databricks-Machine-Learning-Associate
Exam Name:
Databricks Certified Machine Learning Associate Exam
Certification:
Vendor:
Questions:
74
Last Updated:
Apr 3, 2025
Exam Status:
Stable
Databricks Databricks-Machine-Learning-Associate

Databricks-Machine-Learning-Associate: ML Data Scientist Exam 2025 Study Guide Pdf and Test Engine

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Databricks Certified Machine Learning Associate Exam Questions and Answers

Question 1

An organization is developing a feature repository and is electing to one-hot encode all categorical feature variables. A data scientist suggests that the categorical feature variables should not be one-hot encoded within the feature repository.

Which of the following explanations justifies this suggestion?

Options:

A.

One-hot encoding is not supported by most machine learning libraries.

B.

One-hot encoding is dependent on the target variable's values which differ for each application.

C.

One-hot encoding is computationally intensive and should only be performed on small samples of training sets for individual machine learning problems.

D.

One-hot encoding is not a common strategy for representing categorical feature variables numerically.

E.

One-hot encoding is a potentially problematic categorical variable strategy for some machine learning algorithms.

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Question 2

Which of the following approaches can be used to view the notebook that was run to create an MLflow run?

Options:

A.

Open the MLmodel artifact in the MLflow run paqe

B.

Click the "Models" link in the row corresponding to the run in the MLflow experiment paqe

C.

Click the "Source" link in the row corresponding to the run in the MLflow experiment page

D.

Click the "Start Time" link in the row corresponding to the run in the MLflow experiment page

Question 3

A data scientist uses 3-fold cross-validation when optimizing model hyperparameters for a regression problem. The following root-mean-squared-error values are calculated on each of the validation folds:

• 10.0

• 12.0

• 17.0

Which of the following values represents the overall cross-validation root-mean-squared error?

Options:

A.

13.0

B.

17.0

C.

12.0

D.

39.0

E.

10.0