2025/November Latest Braindump2go DP-100 Exam Dumps with PDF and VCE Free Updated Today! Following are some new Braindump2go DP-100 Real Exam Questions!

QUESTION 149
You have a comma-separated values (CSV) file containing data from which you want to train a classification model.
You are using the Automated Machine Learning interface in Azure Machine Learning studio to train the classification model. You set the task type to Classification.
You need to ensure that the Automated Machine Learning process evaluates only linear models.
What should you do?

A. Add all algorithms other than linear ones to the blocked algorithms list.
B. Set the Exit criterion option to a metric score threshold.
C. Clear the option to perform automatic featurization.
D. Clear the option to enable deep learning.
E. Set the task type to Regression.

Answer: C
Explanation:
Automatic featurization can fit non-linear models.
Reference:
https://econml.azurewebsites.net/spec/estimation/dml.html
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-use-automated-ml-for-ml-models

QUESTION 150
You are a data scientist working for a bank and have used Azure ML to train and register a machine learning model that predicts whether a customer is likely to repay a loan.
You want to understand how your model is making selections and must be sure that the model does not violate government regulations such as denying loans based on where an applicant lives.
You need to determine the extent to which each feature in the customer data is influencing predictions.
What should you do?

A. Enable data drift monitoring for the model and its training dataset.
B. Score the model against some test data with known label values and use the results to calculate a confusion matrix.
C. Use the Hyperdrive library to test the model with multiple hyperparameter values.
D. Use the interpretability package to generate an explainer for the model.
E. Add tags to the model registration indicating the names of the features in the training dataset.

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December/2021 Latest Braindump2go DP-100 Exam Dumps with PDF and VCE Free Updated Today! Following are some new DP-100 Real Exam Questions!

QUESTION 264
You need to consider the underlined segment to establish whether it is accurate.
To improve the amount of low incidence cases in a dataset, you should make use of the SMOTE module.
Select “No adjustment required” if the underlined segment is accurate. If the underlined segment is inaccurate, select the accurate option.

A. No adjustment required.
B. Remove Duplicate Rows
C. Join Data
D. Edit Metadata

Answer: A
Explanation:
Use the SMOTE module in Azure Machine Learning Studio to increase the number of underrepresented cases in a dataset used for machine learning. SMOTE is a better way of increasing the number of rare cases than simply duplicating existing cases.
Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/smote

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2020/November Latest Braindump2go DP-100 Exam Dumps with PDF and VCE Free Updated Today! Following are some new DP-100 Real Exam Questions!

QUESTION 190
You create a batch inference pipeline by using the Azure ML SDK.
You configure the pipeline parameters by executing the following code:

You need to obtain the output from the pipeline execution.
Where will you find the output?

A. the digit_identification.py script
B. the debug log
C. the Activity Log in the Azure portal for the Machine Learning workspace
D. the Inference Clusters tab in Machine Learning studio
E. a file named parallel_run_step.txt located in the output folder

Answer: E
Explanation:
output_action (str): How the output is to be organized. Currently supported values are ‘append_row’ and ‘summary_only’.
‘append_row’ ?All values output by run() method invocations will be aggregated into one unique file named parallel_run_step.txt that is created in the output location.
‘summary_only’
Reference:
https://docs.microsoft.com/en-us/python/api/azureml-contrib-pipeline-steps/ azureml.contrib.pipeline.steps.parallelrunconfig

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May/2020 New Braindump2go DP-100 Exam Dumps with PDF and VCE Free Updated Today! Following are some new DP-100 Exam Questions!

QUESTION 71
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are analyzing a numerical dataset which contain missing values in several columns. You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set.
You need to analyze a full dataset to include all values.
Solution: Use the last Observation Carried Forward (IOCF) method to impute the missing data points.
Does the solution meet the goal?

A. Yes
B. No

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