Microsoft Microsoft Certifications DP-100 Questions & Answers

• Question 211:

  You are planning to host practical training to acquaint learners with data visualization creation using Python. Learner devices are able to connect to the internet.

  Learner devices are currently NOT configured for Python development. Also, learners are unable to install software on their devices as they lack administrator permissions. Furthermore, they are unable to access Azure subscriptions.

  It is imperative that learners are able to execute Python-based data visualization code.

  Which of the following actions should you take?

  A. You should consider configuring the use of Azure Container Instance.

  B. You should consider configuring the use of Azure BatchAI.

  C. You should consider configuring the use of Azure Notebooks.

  D. You should consider configuring the use of Azure Kubernetes Service.

  Correct Answer: C

  Reference: https://notebooks.azure.com/

• Question 212:

  You have recently concluded the construction of a binary classification machine learning model.

  You are currently assessing the model. You want to make use of a visualization that allows for precision to be used as the measurement for the assessment.

  Which of the following actions should you take?

  A. You should consider using Venn diagram visualization.

  B. You should consider using Receiver Operating Characteristic (ROC) curve visualization.

  C. You should consider using Box plot visualization.

  D. You should consider using the Binary classification confusion matrix visualization.

  Correct Answer: D

  Reference: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-understand-automated-ml#confusion-matrix

• Question 213:

  You have been tasked with evaluating your model on a partial data sample via k-fold cross-validation.

  You have already configured a k parameter as the number of splits. You now have to configure the k parameter for the cross-validation with the usual value choice.

  Recommendation: You configure the use of the value k=1.

  Will the requirements be satisfied?

  A. Yes

  B. No

  Correct Answer: B

• Question 214:

  You need to consider the underlined segment to establish whether it is accurate.

  To transform a categorical feature into a binary indicator, you should make use of the Clean Missing Data 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. Convert to Indicator Values

  C. Apply SQL Transformation

  D. Group Categorical Values

  Correct Answer: B

  Use the Convert to Indicator Values module in Azure Machine Learning Studio. The purpose of this module is to convert columns that contain categorical values into a series of binary indicator columns that can more easily be used as features in a machine learning model.

  Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/convert-to-indicator-values

• Question 215:

  You are in the process of creating a machine learning model. Your dataset includes rows with null and missing values.

  You plan to make use of the Clean Missing Data module in Azure Machine Learning Studio to detect and fix the null and missing values in the dataset.

  Recommendation: You make use of the Remove entire row option.

  Will the requirements be satisfied?

  A. Yes

  B. No

  Correct Answer: A

  Remove entire row: Completely removes any row in the dataset that has one or more missing values. This is useful if the missing value can be considered randomly missing. Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data

• Question 216:

  You have been tasked with creating a new Azure pipeline via the Machine Learning designer.

  You have to makes sure that the pipeline trains a model using data in a comma-separated values (CSV) file that is published on a website. A dataset for the file for this file does not exist.

  Data from the CSV file must be ingested into the designer pipeline with the least amount of administrative effort as possible.

  Which of the following actions should you take?

  A. You should make use of the Convert to TXT module.

  B. You should add the Copy Data object to the pipeline.

  C. You should add the Import Data object to the pipeline.

  D. You should add the Dataset object to the pipeline.

  Correct Answer: D

  The preferred way to provide data to a pipeline is a Dataset object. The Dataset object points to data that lives in or is accessible from a datastore or at a Web URL. The Dataset class is abstract, so you will create an instance of either a

  FileDataset (referring to one or more files) or a TabularDataset that's created by from one or more files with delimited columns of data.

  Example:

  from azureml.core import Dataset

  iris_tabular_dataset = Dataset.Tabular.from_delimited_files([(def_blob_store, 'train-dataset/iris.csv')])

  Reference:

  https://docs.microsoft.com/en-us/azure/machine-learning/how-to-create-your-first-pipeline

• Question 217:

  You are in the process of creating a machine learning model. Your dataset includes rows with null and missing values.

  You plan to make use of the Clean Missing Data module in Azure Machine Learning Studio to detect and fix the null and missing values in the dataset.

  Recommendation: You make use of the Replace with median option.

  Will the requirements be satisfied?

  A. Yes

  B. No

  Correct Answer: B

  Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data

• Question 218:

  You are in the process of creating a machine learning model. Your dataset includes rows with null and missing values.

  You plan to make use of the Clean Missing Data module in Azure Machine Learning Studio to detect and fix the null and missing values in the dataset.

  Recommendation: You make use of the Custom substitution value option.

  Will the requirements be satisfied?

  A. Yes

  B. No

  Correct Answer: B

  Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data

• Question 219:

  You have been tasked with evaluating your model on a partial data sample via k-fold cross-validation.

  You have already configured a k parameter as the number of splits. You now have to configure the k parameter for the cross-validation with the usual value choice.

  Recommendation: You configure the use of the value k=3.

  Will the requirements be satisfied?

  A. Yes

  B. No

  Correct Answer: B

• Question 220:

  You have been tasked with evaluating your model on a partial data sample via k-fold cross-validation.

  You have already configured a k parameter as the number of splits. You now have to configure the k parameter for the cross-validation with the usual value choice.

  Recommendation: You configure the use of the value k=10.

  Will the requirements be satisfied?

  A. Yes

  B. No

  Correct Answer: A

  Leave One Out (LOO) cross-validation

  Setting K = n (the number of observations) yields n-fold and is called leave-one out cross-validation (LOO), a special case of the K-fold approach.

  LOO CV is sometimes useful but typically doesn't shake up the data enough. The estimates from each fold are highly correlated and hence their average can have high variance.

  This is why the usual choice is K=5 or 10. It provides a good compromise for the bias-variance tradeoff.