DP-100受験対策書、DP-100模擬練習 - Microsoft DP-100問題無料 - Omgzlook

OmgzlookのMicrosoftのDP-100受験対策書試験トレーニング資料を利用して気楽に試験に合格しました。それはコストパフォーマンスが非常に高い資料ですから、もしあなたも私と同じIT夢を持っていたら、OmgzlookのMicrosoftのDP-100受験対策書試験トレーニング資料を利用してください。それはあなたが夢を実現することを助けられます。 Omgzlookがそんなに良いトレーニング資料を提供してあげることを感謝すべきです。Omgzlookはあなたが方途を失うときにヘルプを提供します。 さて、はやく試験を申し込みましょう。

Microsoft Azure DP-100 確かに、これは困難な試験です。

Microsoft Azure DP-100受験対策書 - Designing and Implementing a Data Science Solution on Azure もちろんありますよ。 試験に準備する方法が色々ありますが、最も高効率なのは、きっと良いツールを利用することですね。ところで、あなたにとってどんなツールが良いと言えるのですか。

OmgzlookのMicrosoftのDP-100受験対策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す。君がMicrosoftのDP-100受験対策書問題集を購入したら、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。もしMicrosoftのDP-100受験対策書問題集は問題があれば、或いは試験に不合格になる場合は、全額返金することを保証いたします。

Microsoft DP-100受験対策書 - Omgzlookには専門的なエリート団体があります。

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DP-100 PDF DEMO:

QUESTION NO: 1
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: 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 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: 4
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

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 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

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Updated: May 28, 2022