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MicrosoftのDP-100認定内容試験に合格したいんですか。
どのようにMicrosoft DP-100 - Designing and Implementing a Data Science Solution on Azure認定内容試験に準備すると悩んでいますか。 しかし、我々Goldmile-Infobizチームは力を尽くしてあなたのMicrosoftのDP-100 試験準備試験を準備する圧力を減少して規範的な模擬問題と理解しやすい解答分析はあなたにMicrosoftのDP-100 試験準備試験に合格するコツを把握させます。試験に失敗したら、あなたのMicrosoftのDP-100 試験準備試験の成績書を提供して確認してから我々はすべての費用をあなたに払い戻します。
あなたはDP-100認定内容練習問題を選ばれば、試験に合格できますよ！ローマは一日に建てられませんでした。多くの人にとって、短い時間でDP-100認定内容試験に合格できることは難しいです。
Microsoft DP-100認定内容 - こうして、君は安心で試験の準備を行ってください。
今多くのIT技術会社は職員がMicrosoftのDP-100認定内容資格認定を持つのを要求します。MicrosoftのDP-100認定内容試験に合格するのは必要なことになります。速く試験に合格して資格認証を取得したいなら、我々Goldmile-InfobizのDP-100認定内容問題集を使ってみてください。弊社はあなたに相応しくて品質高いDP-100認定内容問題集を提供します。また、あなたの持っている問題集は一年間の無料更新を得られています。あなたは十分の時間でDP-100認定内容試験を準備することができます。
Goldmile-Infobizが提供したMicrosoftのDP-100認定内容「Designing and Implementing a Data Science Solution on Azure」試験問題と解答が真実の試験の練習問題と解答は最高の相似性があり、一年の無料オンラインの更新のサービスがあり、100%のパス率を保証して、もし試験に合格しないと、弊社は全額で返金いたします。
DP-100 PDF DEMO:
QUESTION NO: 1
You need to define an evaluation strategy for the crowd sentiment models.
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: Define a cross-entropy function activation
When using a neural network to perform classification and prediction, it is usually better to use cross- entropy error than classification error, and somewhat better to use cross-entropy error than mean squared error to evaluate the quality of the neural network.
Step 2: Add cost functions for each target state.
Step 3: Evaluated the distance error metric.
References:
https://www.analyticsvidhya.com/blog/2018/04/fundamentals-deep-learning-regularization- techniques/
QUESTION NO: 2
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
QUESTION NO: 3
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: 4
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: 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