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DP-100 Practice Questions

Question # 1
You use the Azure Machine learning SDK v2 tor Python and notebooks to tram a model. You use Python code to create a compute target, an environment, and a taring script. You need to prepare information to submit a training job. Which class should you use?
A. MLClient
B. command
C. BuildContext
D. EndpointConnection


B. command


Question # 2
You are building a machine learning model for translating English language textual content into French language textual content. You need to build and train the machine learning model to learn the sequence of the textual content. Which type of neural network should you use?
A. Multilayer Perceptions (MLPs)
B. Convolutional Neural Networks (CNNs)
C. Recurrent Neural Networks (RNNs)
D. Generative Adversarial Networks (GANs)


C. Recurrent Neural Networks (RNNs)

Explanation:

To translate a corpus of English text to French, we need to build a recurrent neural network (RNN).

Note: RNNs are designed to take sequences of text as inputs or return sequences of text as outputs, or both.

They’re called recurrent because the network’s hidden layers have a loop in which the output and cell state from each time step become inputs at the next time step. This recurrence serves as a form of memory. It allows contextual information to flow through the network so that relevant outputs from previous time steps can be applied to network operations at the current time step.

References:

https://towardsdatascience.com/language-translation-with-rnns-d84d43b40571

Question # 3
You are using Azure Machine Learning to monitor a trained and deployed model. You implement Event Grid to respond to Azure Machine Learning events. Model performance has degraded due to model input data changes. You need to trigger a remediation ML pipeline based on an Azure Machine Learning event. Which event should you use?
A. RunStatusChanged
B. DatasetDriftDetected
C. ModelDeployed
D. RunCompleted


B. DatasetDriftDetected


Question # 4
You plan to provision an Azure Machine Learning Basic edition workspace for a data science project. You need to identify the tasks you will be able to perform in the workspace. Which three tasks will you be able to perform? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.
A. Create a Compute Instance and use it to run code in Jupyter notebooks.
B. Create an Azure Kubernetes Service (AKS) inference cluster.
C. Use the designer to train a model by dragging and dropping pre-defined modules.
D. Create a tabular dataset that supports versioning.
E. Use the Automated Machine Learning user interface to train a model.


A. Create a Compute Instance and use it to run code in Jupyter notebooks.
B. Create an Azure Kubernetes Service (AKS) inference cluster.
D. Create a tabular dataset that supports versioning.

Explanation:

[Reference:, https://azure.microsoft.com/en-us/pricing/details/machine-learning/, , , ]

Question # 5
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 have an Azure Machine Learning workspace. You connect to a terminal session from the Notebooks page in Azure Machine Learning studio.

You plan to add a new Jupyter kernel that will be accessible from the same terminal session.

You need to perform the task that must be completed before you can add the new kernel.

Solution: Delete the Python 3.8 - AzureML kernel.

Does the solution meet the goal?

A. Yes
B. No


B. No


Question # 6
You need to select a feature extraction method. Which method should you use?
A. Spearman correlation
B. Mutual information
C. Mann-Whitney test
D. Pearson’s correlation


A. Spearman correlation

Explanation:

Spearman's rank correlation coefficient assesses how well the relationship between two variables can be described using a monotonic function.

Note: Both Spearman's and Kendall's can be formulated as special cases of a more general correlation coefficient, and they are both appropriate in this scenario.

Scenario: The MedianValue and AvgRoomsInHouse columns both hold data in numeric format. You need to select a feature selection algorithm to analyze the relationship between the two columns in more detail.

References:

https://docs.microsoft.com/en-us/azure/machine-lear ning/studio-module-reference/feature-selection-modules


Question # 7
You use Azure Machine Learning to train a model based on a dataset named dataset1. You define a dataset monitor and create a dataset named dataset2 that contains new data. You need to compare dataset1 and dataset2 by using the Azure Machine Learning SDK for Python. Which method of the DataDriftDetector class should you use?
A. run
B. get
C. backfill
D. update


C. backfill

Explanation:

A backfill run is used to see how data changes over time.

[Reference:, https://docs.microsoft.com/en-us/python/api/azureml-datadrift/azureml.datadrift.datadriftdetector.datadriftdetector, , ]


Question # 8
You are creating a new experiment in Azure Machine Learning Studio. You have a small dataset that has missing values in many columns. The data does not require the application of predictors for each column. You plan to use the Clean Missing Data module to handle the missing data. You need to select a data cleaning method. Which method should you use?
A. Synthetic Minority Oversampling Technique (SMOTE)
B. Replace using MICE
C. Replace using; Probabilistic PCA
D. Normalization


C. Replace using; Probabilistic PCA

Explanation:

Replace using Probabilistic PCA: Compared to other options, such as Multiple Imputation using Chained Equations (MICE), this option has the advantage of not requiring the application of predictors for each column. Instead, it approximates the covariance for the full dataset. Therefore, it might offer better performance for datasets that have missing values in many columns.

References:

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


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Exam Name: Designing and Implementing a Data Science Solution on Azure Exam
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