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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 26, 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

A machine learning engineering team has a Job with three successive tasks. Each task runs a single notebook. The team has been alerted that the Job has failed in its latest run.

Which of the following approaches can the team use to identify which task is the cause of the failure?

Options:

A.

Run each notebook interactively

B.

Review the matrix view in the Job's runs

C.

Migrate the Job to a Delta Live Tables pipeline

D.

Change each Task’s setting to use a dedicated cluster

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Question 2

A data scientist is using Spark ML to engineer features for an exploratory machine learning project.

They decide they want to standardize their features using the following code block:

Upon code review, a colleague expressed concern with the features being standardized prior to splitting the data into a training set and a test set.

Which of the following changes can the data scientist make to address the concern?

Options:

A.

Utilize the MinMaxScaler object to standardize the training data according to global minimum and maximum values

B.

Utilize the MinMaxScaler object to standardize the test data according to global minimum and maximum values

C.

Utilize a cross-validation process rather than a train-test split process to remove the need for standardizing data

D.

Utilize the Pipeline API to standardize the training data according to the test data's summary statistics

E.

Utilize the Pipeline API to standardize the test data according to the training data's summary statistics

Question 3

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