DP-100공부자료 - Microsoft Designing And Implementing A Data Science Solution On Azure시험응시료 - Omgzlook

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Microsoft Azure DP-100 완벽한 관연 지식터득은 물론입니다.

Omgzlook는 자격증 응시자에게Microsoft DP-100 - Designing and Implementing a Data Science Solution on Azure공부자료 시험 준비를 위한 현재 그리고 가장 최근의 자료들을 제공하는 이 산업 영역의 리더입니다. Microsoft DP-100 질문과 답인증시험은 현재IT업계에서 아주 인기 있는 시험입니다.많은 IT인사들이 관연 자격증을 취득하려고 노력하고 있습니다.Microsoft DP-100 질문과 답인증시험에 대한 열기는 식지 않습니다.Microsoft DP-100 질문과 답자격증은 여러분의 사회생활에 많은 도움이 될 것이며 연봉상승 등 생활보장에 업그레이드 될 것입니다.

여러분은Microsoft DP-100공부자료인증시험을 패스함으로 IT업계관련 직업을 찿고자하는 분들에게는 아주 큰 가산점이 될수 있으며, 성덩한 IT업계사업자와 한걸음 가까와 집니다.

Microsoft DP-100공부자료 - 많은 시간과 돈이 필요 없습니다.

Microsoft인증 DP-100공부자료시험은 IT인증시험중 가장 인기있는 시험입니다. Microsoft인증 DP-100공부자료시험패스는 모든 IT인사들의 로망입니다. Omgzlook의 완벽한 Microsoft인증 DP-100공부자료덤프로 시험준비하여 고득점으로 자격증을 따보세요.

Microsoft 인증 DP-100공부자료시험뿐만 아니라 IT인증시험에 관한 모든 시험에 대비한 덤프를 제공해드립니다. 많은 애용 바랍니다.

DP-100 PDF DEMO:

QUESTION NO: 1
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 are a data scientist using Azure Machine Learning Studio.
You need to normalize values to produce an output column into bins to predict a target column.
Solution: Apply a Quantiles normalization with a QuantileIndex normalization.
Does the solution meet the GOAL?
A. Yes
B. No
Answer: B
Explanation:
Use the Entropy MDL binning mode which has a target column.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/group-data- into-bins

QUESTION NO: 2
You create a binary classification model by using Azure Machine Learning Studio.
You must tune hyperparameters by performing a parameter sweep of the model. The parameter sweep must meet the following requirements:
* iterate all possible combinations of hyperparameters
* minimize computing resources required to perform the sweep
* You need to perform a parameter sweep of the model.
Which parameter sweep mode should you use?
A. Sweep clustering
B. Entire grid
C. Random grid
D. Random seed
E. Random sweep
Answer: C
Explanation:
Maximum number of runs on random grid: This option also controls the number of iterations over a random sampling of parameter values, but the values are not generated randomly from the specified range; instead, a matrix is created of all possible combinations of parameter values and a random sampling is taken over the matrix. This method is more efficient and less prone to regional oversampling or undersampling.
If you are training a model that supports an integrated parameter sweep, you can also set a range of seed values to use and iterate over the random seeds as well. This is optional, but can be useful for avoiding bias introduced by seed selection.
Incorrect Answers:
B: If you are building a clustering model, use Sweep Clustering to automatically determine the optimum number of clusters and other parameters.
C: Entire grid: When you select this option, the module loops over a grid predefined by the system, to try different combinations and identify the best learner. This option is useful for cases where you don't know what the best parameter settings might be and want to try all possible combination of values.
E: If you choose a random sweep, you can specify how many times the model should be trained, using a random combination of parameter values.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/tune-model- hyperparameters

QUESTION NO: 3
You are performing feature engineering on a dataset.
You must add a feature named CityName and populate the column value with the text London.
You need to add the new feature to the dataset.
Which Azure Machine Learning Studio module should you use?
A. Preprocess Text
B. Edit Metadata
C. Execute Python Script
D. Latent Dirichlet Allocation
Answer: B
Explanation:
Typical metadata changes might include marking columns as features.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/edit-metadata

QUESTION NO: 4
You are developing a hands-on workshop to introduce Docker for Windows to attendees.
You need to ensure that workshop attendees can install Docker on their devices.
Which two prerequisite components should attendees install on the devices? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. Windows 10 64-bit Professional
B. Kitematic
C. BIOS-enabled virtualization
D. VirtualBox
E. Microsoft Hardware-Assisted Virtualization Detection Tool
Answer: A,C
Explanation:
C: Make sure your Windows system supports Hardware Virtualization Technology and that virtualization is enabled.
Ensure that hardware virtualization support is turned on in the BIOS settings. For example:
E: To run Docker, your machine must have a 64-bit operating system running Windows 7 or higher.
References:
https://docs.docker.com/toolbox/toolbox_install_windows/
https://blogs.technet.microsoft.com/canitpro/2015/09/08/step-by-step-enabling-hyper-v-for-use- on-windows-10/

QUESTION NO: 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 are a data scientist using Azure Machine Learning Studio.
You need to normalize values to produce an output column into bins to predict a target column.
Solution: Apply an Equal Width with Custom Start and Stop binning mode.
Does the solution meet the goal?
A. Yes
B. No
Answer: B
Explanation:
Use the Entropy MDL binning mode which has a target column.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/group-data- into-bins

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Updated: May 28, 2022