IT業界での競争がますます激しくなるうちに、あなたの能力をどのように証明しますか。MicrosoftのDP-100資格勉強試験に合格するのは説得力を持っています。我々ができるのはあなたにより速くMicrosoftのDP-100資格勉強試験に合格させます。 世界各地の人々はMicrosoftのDP-100資格勉強認定試験が好きです。この認証は自分のキャリアを強化することができ、自分が成功に近づかせますから。 それでは、DP-100資格勉強試験に参加しよう人々は弊社Goldmile-InfobizのDP-100資格勉強問題集を選らんで勉強して、一発合格して、MicrosoftIT資格証明書を受け取れます。
Microsoft Azure DP-100 」と感謝します。
Microsoft Azure DP-100資格勉強 - Designing and Implementing a Data Science Solution on Azure それはあなたがいつでも最新の試験資料を持てるということです。 有効的なMicrosoft DP-100 資格講座認定資格試験問題集を見つけられるのは資格試験にとって重要なのです。我々Goldmile-InfobizのMicrosoft DP-100 資格講座試験問題と試験解答の正確さは、あなたの試験準備をより簡単にし、あなたが試験に高いポイントを得ることを保証します。
この資料を手に入れたら、楽に試験の準備をすることができます。MicrosoftのDP-100資格勉強試験の準備をしていたら、Goldmile-Infobizは貴方が夢を実現することにヘルプを与えます。Goldmile-InfobizのMicrosoftのDP-100資格勉強試験トレーニング資料は高品質のトレーニング資料で、１００パーセントの合格率を保証できます。
Microsoft DP-100資格勉強 - 本当に助かりました。
それぞれのIT認証試験を受ける受験生の身近な利益が保障できるために、Goldmile-Infobizは受験生のために特別に作成されたMicrosoftのDP-100資格勉強試験トレーニング資料を提供します。この資料はGoldmile-InfobizのIT専門家たちに特別に研究されたものです。彼らの成果はあなたが試験に合格することを助けるだけでなく、あなたにもっと美しい明日を与えることもできます。
Goldmile-Infobizが提供した問題集を利用してMicrosoftのDP-100資格勉強試験は全然問題にならなくて、高い点数で合格できます。Microsoft DP-100資格勉強試験の合格のために、Goldmile-Infobizを選択してください。
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