EXAM DP-100 QUICK PREP - DP-100 EXAM FORMAT

Exam DP-100 Quick Prep - DP-100 Exam Format

Exam DP-100 Quick Prep - DP-100 Exam Format

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Tags: Exam DP-100 Quick Prep, DP-100 Exam Format, Reliable DP-100 Exam Camp, DP-100 Reliable Dump, DP-100 Valid Practice Materials

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Basic Exam Traits

The Microsoft DP-100 is an associate-level job role-based exam. Its structure is the same as any other exam falling in this category. As per the standard test format, DP-100 exam is likely to contain 40-60 exam questions. As far as question format is concerned, Microsoft doesn’t follow a set pattern. The exam is likely to cover questions based on the MCQ pattern. However, the odds of including items based on other patterns like case studies and best answers are also high. What’s more, there is no exact passing score as there is no fixed number of questions and it might change as per the final number of tasks. Nonetheless, a test-taker must secure 70% passing marks to be called successful in the official exam. Currently, this test can be taken in English, Japanese, Chinese (Simplified), and Korean worldwide. The standard exam fee is $165 and is likely to get changed as per the location of the test-taker.

>> Exam DP-100 Quick Prep <<

DP-100 Exam Format, Reliable DP-100 Exam Camp

These practice exams are solely designed to help you achieve DP-100 certification on the first attempt. The mock exam simulator helps you get through every topic inside out and you get overall better grades. This is because you have hands-on the most updated and most reliable Microsoft DP-100 Questions created under the supervision of 90,000 Microsoft professionals.

Microsoft DP-100 Certification Exam is a valuable credential for data scientists and machine learning engineers who want to demonstrate their proficiency in designing and implementing data science solutions on Azure. DP-100 exam covers a wide range of topics related to data science and machine learning and requires candidates to have a deep understanding of Azure data services. To prepare for the exam, candidates can take advantage of various resources provided by Microsoft, including online training courses, study guides, and practice exams.

Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q126-Q131):

NEW QUESTION # 126
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 # 127
You register the following versions of a model.

You use the Azure ML Python SDK to run a training experiment. You use a variable named run to reference the experiment run.
After the run has been submitted and completed, you run the following code:

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:
Explanation

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-deploy-and-where


NEW QUESTION # 128
You have the following Azure subscriptions and Azure Machine Learning service workspaces:

You need to obtain a reference to the mi-protect workspace
Solution: Run the following Python code.

Does the solution meet the goal?

  • A. Yes
  • B. No

Answer: A


NEW QUESTION # 129
You are producing a multiple linear regression model in Azure Machine Learning Studio.
Several independent variables are highly correlated.
You need to select appropriate methods for conducting effective feature engineering on all the data.
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:

Explanation:
Step 1: Use the Filter Based Feature Selection module
Filter Based Feature Selection identifies the features in a dataset with the greatest predictive power.
The module outputs a dataset that contains the best feature columns, as ranked by predictive power. It also outputs the names of the features and their scores from the selected metric.
Step 2: Build a counting transform
A counting transform creates a transformation that turns count tables into features, so that you can apply the transformation to multiple datasets.
Step 3: Test the hypothesis using t-Test
References:
https://docs.microsoft.com/bs-latn-ba/azure/machine-learning/studio-module-reference/filter-based-feature-selection
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/build-counting-transform


NEW QUESTION # 130
You train and register a model in your Azure Machine Learning workspace.
You must publish a pipeline that enables client applications to use the model for batch inferencing. You must use a pipeline with a single ParallelRunStep step that runs a Python inferencing script to get predictions from the input data.
You need to create the inferencing script for the ParallelRunStep pipeline step.
Which two functions should you include? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

  • A. run(mini_batch)
  • B. batch()
  • C. init()
  • D. score(mini_batch)
  • E. main()

Answer: A,C

Explanation:
https://github.com/Azure/MachineLearningNotebooks/tree/master/how-to-use-azureml/machine- learning-pipelines/parallel-run


NEW QUESTION # 131
......

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