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Microsoft Azure DP-100 それは問題ではないですよ。
OmgzlookのMicrosoftのDP-100 - Designing and Implementing a Data Science Solution on Azure受験練習参考書試験トレーニング資料を持っていたら、試験に対する充分の準備がありますから、安心に利用したください。 IT認定試験の中でどんな試験を受けても、OmgzlookのDP-100 日本語版参考資料試験参考資料はあなたに大きなヘルプを与えることができます。それは OmgzlookのDP-100 日本語版参考資料問題集には実際の試験に出題される可能性がある問題をすべて含んでいて、しかもあなたをよりよく問題を理解させるように詳しい解析を与えますから。
これは試験の準備をするために非常に効率的なツールですから。この問題集はあなたが少ない労力で最高の結果を取得することができます。OmgzlookはIT認定試験を受験した多くの人々を助けました。
Microsoft DP-100受験練習参考書 - 私たちは君がITエリートになるのに頑張ります。
一回だけでMicrosoftのDP-100受験練習参考書試験に合格したい？Omgzlookは君の欲求を満たすために存在するのです。Omgzlookは君にとってベストな選択になります。ここには、私たちは君の需要に応じます。OmgzlookのMicrosoftのDP-100受験練習参考書問題集を購入したら、私たちは君のために、一年間無料で更新サービスを提供することができます。もし不合格になったら、私たちは全額返金することを保証します。
Omgzlookでは、私たちは君のすべての夢を叶えさせて、君の最も早い時間でMicrosoftのDP-100受験練習参考書認定試験に合格するということを保証します。OmgzlookのMicrosoftのDP-100受験練習参考書試験トレーニング資料は豊富な経験を持っているIT専門家が研究したもので、問題と解答が緊密に結んでいるものです。
DP-100 PDF DEMO:
QUESTION NO: 1
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: 2
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: 3
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: 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