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Microsoft Azure DP-100 弊社の量豊かの備考資料はあなたを驚かさせます。
Microsoft Azure DP-100問題例 - Designing and Implementing a Data Science Solution on Azure Omgzlookはあなたの夢に実現させるサイトでございます。 我々社のMicrosoft DP-100 必殺問題集問題集とサーブすが多くの人々に認められます。最近、Microsoft DP-100 必殺問題集問題集は通過率が高いなので大人気になります。
Omgzlookの専門家チームが君の需要を満たすために自分の経験と知識を利用してMicrosoftのDP-100問題例認定試験対策模擬テスト問題集が研究しました。模擬テスト問題集と真実の試験問題がよく似ています。一目でわかる最新の出題傾向でわかりやすい解説と充実の補充問題があります。
Microsoft DP-100問題例 - そうだったら、下記のものを読んでください。
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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。
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
MicrosoftのJuniper JN0-683認証試験は世界でどの国でも承認されて、すべての国が分け隔てをしないの試験です。 OmgzlookのMicrosoftのHP HPE6-A73J試験トレーニング資料は試験問題と解答を含まれて、豊富な経験を持っているIT業種の専門家が長年の研究を通じて作成したものです。 OmgzlookのMicrosoftのIIA IIA-CIA-Part2-JPN「Designing and Implementing a Data Science Solution on Azure」トレーニング資料を利用したら、初めて試験を受けるあなたでも一回で試験に合格できることを保証します。 EMC D-PEMX-DY-23 - 我々の誠意を信じてください。 SAP C-HRHPC-2405 - それに、会社に大量な人的·物的資源を節約させると同時に、案外のうまい効果を取得しました。
Updated: May 28, 2022