弊社の誠意を信じてもらいたいし、Microsoft DP-100資格試験試験2成功するのを祈って願います。大量の時間と金銭をかかるのに比べて、正しい仕方は肝心なことです。もしあなたはMicrosoft DP-100資格試験試験に準備しているなら、あんたのための整理される備考資料はあなたにとって最善のオプションです。 私の夢は最高のIT専門家になることです。その夢は私にとってはるか遠いです。 短時間で一度に本当の認定試験に高いポイントを取得したいなら、我々OmgzlookのMicrosoft DP-100資格試験日本語対策問題集は絶対にあなたへの最善なオプションです。
Microsoft Azure DP-100 あなたの夢は何ですか。
Microsoft Azure DP-100資格試験 - Designing and Implementing a Data Science Solution on Azure そうすれば、わかりやすく、覚えやすいです。 OmgzlookのDP-100 練習問題教材を購入したら、あなたは一年間の無料アップデートサービスを取得しました。試験問題集が更新されると、Omgzlookは直ちにあなたのメールボックスにDP-100 練習問題問題集の最新版を送ります。
Microsoft DP-100資格試験認証試験を通るために、いいツールが必要です。Microsoft DP-100資格試験認証試験について研究の資料がもっとも大部分になって、Omgzlookは早くてMicrosoft DP-100資格試験認証試験の資料を集めることができます。弊社の専門家は経験が豊富で、研究した問題集がもっとも真題と近づいて現場試験のうろたえることを避けます。
Microsoft DP-100資格試験 - Microsoftの試験はどうですか。
MicrosoftのDP-100資格試験認定試験に受かるのはあなたの技能を検証することだけでなく、あなたの専門知識を証明できて、上司は無駄にあなたを雇うことはしないことの証明書です。当面、IT業界でMicrosoftのDP-100資格試験認定試験の信頼できるソースが必要です。Omgzlookはとても良い選択で、DP-100資格試験の試験を最も短い時間に縮められますから、あなたの費用とエネルギーを節約することができます。それに、あなたに美しい未来を作ることに助けを差し上げられます。
それと比べるものがありません。専門的な団体と正確性の高いMicrosoftのDP-100資格試験問題集があるこそ、Omgzlookのサイトは世界的でDP-100資格試験試験トレーニングによっての試験合格率が一番高いです。
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