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Microsoft Azure DP-100 永遠不要說你已經盡力了。
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Microsoft DP-100題庫更新資訊認證考試在競爭激烈的IT行業中越來越受歡迎，報名參加考試的人越來越多。但是它的難度並沒有減小，依然很難通過考試，畢竟這是個權威的檢驗電腦專業知識和資訊技術能力的考試。一般人為了通過Microsoft DP-100題庫更新資訊 認證考試都需要花費大量的時間和精力來復習備考。
Microsoft DP-100題庫更新資訊 - 比賽是這樣，同樣考試也是這樣的。
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但是，和考試的重要性一樣，這個考試也是非常難的。要通过考试是有些难，但是不用担心。
DP-100 PDF DEMO:
QUESTION NO: 1
You use Azure Machine Learning Studio to build a machine learning experiment.
You need to divide data into two distinct datasets.
Which module should you use?
A. Test Hypothesis Using t-Test
B. Group Data into Bins
C. Assign Data to Clusters
D. Partition and Sample
Answer: D
Explanation:
Partition and Sample with the Stratified split option outputs multiple datasets, partitioned using the rules you specified.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/partition-and- sample
QUESTION NO: 2
You are developing a machine learning, experiment by using Azure. The following images show the input and output of a machine learning experiment:
Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.
Answer:
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 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: 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
You need to define a modeling strategy for ad response.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Step 1: Implement a K-Means Clustering model
Step 2: Use the cluster as a feature in a Decision jungle model.
Decision jungles are non-parametric models, which can represent non-linear decision boundaries.
Step 3: Use the raw score as a feature in a Score Matchbox Recommender model The goal of creating a recommendation system is to recommend one or more "items" to "users" of the system. Examples of an item could be a movie, restaurant, book, or song. A user could be a person, group of persons, or other entity with item preferences.
Scenario:
Ad response rated declined.
Ad response models must be trained at the beginning of each event and applied during the sporting event.
Market segmentation models must optimize for similar ad response history.
Ad response models must support non-linear boundaries of features.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/multiclass- decision-jungle
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/score- matchbox-recommender
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Updated: May 28, 2022