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Prepare for the Microsoft Designing and Implementing a Data Science Solution on Azure exam with our extensive collection of questions and answers. These practice Q&A are updated according to the latest syllabus, providing you with the tools needed to review and test your knowledge.
QA4Exam focus on the latest syllabus and exam objectives, our practice Q&A are designed to help you identify key topics and solidify your understanding. By focusing on the core curriculum, These Questions & Answers helps you cover all the essential topics, ensuring you're well-prepared for every section of the exam. Each question comes with a detailed explanation, offering valuable insights and helping you to learn from your mistakes. Whether you're looking to assess your progress or dive deeper into complex topics, our updated Q&A will provide the support you need to confidently approach the Microsoft DP-100 exam and achieve success.
The questions for DP-100 were last updated on Nov 19, 2024.
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You need to implement a new cost factor scenario for the ad response models as illustrated in the
performance curve exhibit.
Which technique should you use?
Scenario:
Performance curves of current and proposed cost factor scenarios are shown in the following diagram:
The ad propensity model uses a cut threshold is 0.45 and retrains occur if weighted Kappa deviated from 0.1 +/- 5%.
You are moving a large dataset from Azure Machine Learning Studio to a Weka environment.
You need to format the data for the Weka environment.
Which module should you use?
Use the Convert to ARFF module in Azure Machine Learning Studio, to convert datasets and results in Azure Machine Learning to the attribute-relation file format used by the Weka toolset. This format is known as ARFF.
The ARFF data specification for Weka supports multiple machine learning tasks, including data preprocessing, classification, and feature selection. In this format, data is organized by entites and their attributes, and is contained in a single text file.
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/convert-to-arff
You create an Azure Machine Learning workspace. You use Azure Machine Learning designer to create a pipeline within the workspace. You need to submit a pipeline run from the designer.
What should you do first?
You are analyzing a dataset containing historical data from a local taxi company. You arc developing a regression a regression model.
You must predict the fare of a taxi trip.
You need to select performance metrics to correctly evaluate the- regression model.
Which two metrics can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
You run a script as an experiment in Azure Machine Learning.
You have a Run object named run that references the experiment run. You must review the log files that were generated during the experiment run.
You need to download the log files to a local folder for review.
Which two code segments can you run to achieve this goal? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
The run Class get_all_logs method downloads all logs for the run to a directory.
The run Class get_details gets the definition, status information, current log files, and other details of the run.
https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.run(class)
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