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Microsoft Azure DP-100 早速買いに行きましょう。
あなたがMicrosoftのDP-100 - Designing and Implementing a Data Science Solution on Azure問題サンプル「Designing and Implementing a Data Science Solution on Azure」認定試験に合格する需要を我々はよく知っていますから、あなたに高品質の問題集と科学的なテストを提供して、あなたが気楽に認定試験に受かることにヘルプを提供するのは我々の約束です。 それは正確性が高くて、カバー率も広いです。あなたはOmgzlookの学習教材を購入した後、私たちは一年間で無料更新サービスを提供することができます。
このトレーニングはカバー率が高いですから、あなたの知識を豊富させる以外、操作レベルを高められます。もし今あなたがMicrosoftのDP-100問題サンプル「Designing and Implementing a Data Science Solution on Azure」試験にどうやって合格することに困っているのなら、心配しないでください。Omgzlookが提供したMicrosoftのDP-100問題サンプルトレーニング資料はあなたの問題を解決することができますから。
Microsoft DP-100問題サンプル - 今はそのようにしていますか。
近年、IT領域で競争がますます激しくなります。IT認証は同業種の欠くことができないものになりました。あなたはキャリアで良い昇進のチャンスを持ちたいのなら、OmgzlookのMicrosoftのDP-100問題サンプル「Designing and Implementing a Data Science Solution on Azure」試験トレーニング資料を利用してMicrosoftの認証の証明書を取ることは良い方法です。現在、MicrosoftのDP-100問題サンプル認定試験に受かりたいIT専門人員がたくさんいます。Omgzlookの試験トレーニング資料はMicrosoftのDP-100問題サンプル認定試験の１００パーセントの合格率を保証します。
でも、利用したことがありますか。「OmgzlookのDP-100問題サンプル問題集は本当に良い教材です。
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 creating a new experiment in Azure Machine Learning Studio.
One class has a much smaller number of observations than the other classes in the training set.
You need to select an appropriate data sampling strategy to compensate for the class imbalance.
Solution: You use the Scale and Reduce sampling mode.
Does the solution meet the goal?
A. No
B. Yes
Answer: A
Explanation:
Instead use the Synthetic Minority Oversampling Technique (SMOTE) sampling mode.
Note: SMOTE is used to increase the number of underepresented cases in a dataset used for machine learning. SMOTE is a better way of increasing the number of rare cases than simply duplicating existing cases.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/smote
EMC D-RP-OE-A-24 - Omgzlookに会ったら、最高のトレーニング資料を見つけました。 SAP C-BW4H-2404 - もし不合格になる場合は、ご心配なく、私たちは資料の費用を全部返金します。 Microsoft MD-102-JPN - 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。 初心者にしても、サラリーマンにしても、Omgzlookは君のために特別なMicrosoftのMicrosoft SC-100問題集を提供します。 CompTIA N10-008 - 気楽に試験に合格したければ、はやく試しに来てください。
Updated: May 28, 2022