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The candidates who want to take the Microsoft DP-100 Exam are expected to have competence in its objectives. This means that they need to understand the scope of topics covered in this certification test. They are as follows:

1. Azure ML Workspace Set-Up (30-35%):

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Microsoft DP-100: Preparation Process

Thorough preparation is an important part of the Microsoft DP-100 Exam and its associate-level certification. Here is the ultimate guide to prepare for this test with great deliberation.

Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q404-Q409):

NEW QUESTION # 404
You create a binary classification model. You use the Fairlearn package to assess model fairness. You must eliminate the need to retrain the model. You need to implement the Fair learn package. Which algorithm should you use?

Answer: A


NEW QUESTION # 405
You need to produce a visualization for the diagnostic test evaluation according to the data visualization requirements.
Which three modules should you recommend be used in sequence? To answer, move the appropriate modules from the list of modules to the answer area and arrange them in the correct order.

Answer:

Explanation:

Explanation

Step 1: Sweep Clustering
Start by using the "Tune Model Hyperparameters" module to select the best sets of parameters for each of the models we're considering.
One of the interesting things about the "Tune Model Hyperparameters" module is that it not only outputs the results from the Tuning, it also outputs the Trained Model.
Step 2: Train Model
Step 3: Evaluate Model
Scenario: You need to provide the test results to the Fabrikam Residences team. You create data visualizations to aid in presenting the results.
You must produce a Receiver Operating Characteristic (ROC) curve to conduct a diagnostic test evaluation of the model. You need to select appropriate methods for producing the ROC curve in Azure Machine Learning Studio to compare the Two-Class Decision Forest and the Two-Class Decision Jungle modules with one another.
References:
http://breaking-bi.blogspot.com/2017/01/azure-machine-learning-model-evaluation.html


NEW QUESTION # 406
You need to modify the inputs for the global penalty event model to address the bias and variance issue.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:

1 - Select the behaviour data.
2 - Add a K-Means clustering module with 10 clusters.
3 - Perform a Primary Component Analysis (PCA).


NEW QUESTION # 407
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: Create an environment.
Does the solution meet the goal?

Answer: A


NEW QUESTION # 408
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?

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


NEW QUESTION # 409
......

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