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What is DP-203 exam?

NEW QUESTION: 1
Your on-premises network contains five file servers. The file servers host shares that contain user data.
You plan to migrate the user data to a Microsoft 36S subscription.
You need to recommend a solution to import the user data into Microsoft OneDrive.
What should you include in the recommendation?
A. Configure the Sync settings in the OneDrive admin center.
B. Run the SharePoint Hybrid Configuration Wizard.
C. Run the SharePoint Migration Tool.
D. Configure the Migrate of the OneDrive client on your Windows 10 device
Answer: C
Explanation:
Explanation
The SharePoint Migration Tool lets you migrate content to SharePoint Online and OneDrive from the following locations:
* SharePoint Server 2013
* SharePoint Server 2010
* Network and local file shares
Reference:
https://docs.microsoft.com/en-us/sharepointmigration/introducing-the-sharepoint-migration-tool

NEW QUESTION: 2
Match the machine learning tasks to the appropriate scenarios.
To answer, drag the appropriate task from the column on the left to its scenario on the right. Each task may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Box 1: Model evaluation
The Model evaluation module outputs a confusion matrix showing the number of true positives, false negatives, false positives, and true negatives, as well as ROC, Precision/Recall, and Lift curves.
Box 2: Feature engineering
Feature engineering is the process of using domain knowledge of the data to create features that help ML algorithms learn better. In Azure Machine Learning, scaling and normalization techniques are applied to facilitate feature engineering. Collectively, these techniques and feature engineering are referred to as featurization.
Note: Often, features are created from raw data through a process of feature engineering. For example, a time stamp in itself might not be useful for modeling until the information is transformed into units of days, months, or categories that are relevant to the problem, such as holiday versus working day.
Box 3: Feature selection
In machine learning and statistics, feature selection is the process of selecting a subset of relevant, useful features to use in building an analytical model. Feature selection helps narrow the field of data to the most valuable inputs. Narrowing the field of data helps reduce noise and improve training performance.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance
https://docs.microsoft.com/en-us/azure/machine-learning/concept-automated-ml

NEW QUESTION: 3
Which language runs natively on the graphics processing unit (GPU)?
A. High Level Shading Language (HLSL)
B. C#
C. JavaScript
D. C++
Answer: A
Explanation:
http://dl.acm.org/citation.cfm?id=2038861&preflayout=tabs