調査、研究を経って、IT職員の月給の増加とジョブのプロモーションはMicrosoft DP-100日本語受験攻略資格認定と密接な関係があります。給料の増加とジョブのプロモーションを真になるために、Goldmile-InfobizのMicrosoft DP-100日本語受験攻略問題集を勉強しましょう。いつまでもDP-100日本語受験攻略試験に準備する皆様に便宜を与えるGoldmile-Infobizは、高品質の試験資料と行き届いたサービスを提供します。 MicrosoftのDP-100日本語受験攻略認証試験を選んだ人々が一層多くなります。DP-100日本語受験攻略試験がユニバーサルになりましたから、あなたはGoldmile-Infobiz のMicrosoftのDP-100日本語受験攻略試験問題と解答￥を利用したらきっと試験に合格するができます。 この目標の達成はあなたがIT技術領域へ行く更なる発展の一歩ですけど、我々社Goldmile-Infobiz存在するこそすべての意義です。
そして、短い時間で勉強し、DP-100日本語受験攻略試験に参加できます。
Microsoft Azure DP-100日本語受験攻略 - Designing and Implementing a Data Science Solution on Azure もし失敗だったら、我々は全額で返金します。 おそらく、君たちは私たちのDP-100 試験準備試験資料について何も知らないかもしれません。でも、私たちのDP-100 試験準備試験資料のデモをダウンロードしてみると、全部わかるようになります。
Goldmile-InfobizのMicrosoftのDP-100日本語受験攻略「Designing and Implementing a Data Science Solution on Azure」試験トレーニング資料はIT職員としてのあなたがIT試験に受かる不可欠なトレーニング資料です。Goldmile-InfobizのMicrosoftのDP-100日本語受験攻略試験トレーニング資料はカバー率が高くて、更新のスピードも速くて、完全なトレーニング資料ですから、Goldmile-Infobiz を手に入れたら、全てのIT認証が恐くなくなります。人生には様々な選択があります。
Microsoft DP-100日本語受験攻略 - Goldmile-Infobizには専門的なエリート団体があります。
もし君がMicrosoftのDP-100日本語受験攻略に参加すれば、良い学習のツルを選ぶすべきです。MicrosoftのDP-100日本語受験攻略認定試験はIT業界の中でとても重要な認証試験で、合格するために良い訓練方法で準備をしなければなりません。。
いろいろな受験生に通用します。あなたはGoldmile-Infobizの学習教材を購入した後、私たちは一年間で無料更新サービスを提供することができます。
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