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有了這個資料你就能輕鬆通過DP-100題庫最新資訊考試，獲得資格認證。
為了配合當前真正的考驗，從Goldmile-Infobiz Microsoft的DP-100 - Designing and Implementing a Data Science Solution on Azure題庫最新資訊考試認證考試考古題的技術團隊的任何變化及時更新的問題和答案，我們也總是接受用戶回饋的問題，充分的利用了一些建議，從而達到完美的Goldmile-Infobiz Microsoft的DP-100 - Designing and Implementing a Data Science Solution on Azure題庫最新資訊考試認證測試資料，使我們Goldmile-Infobiz始終擁有最高的品質。 獲得DP-100 考試大綱認證之后，您的職業生涯也將開始新的輝煌時期。購買我們的Microsoft DP-100 考試大綱題庫資料可以保證考生一次性通過考試，這是值得大家信賴的題庫網站，可以幫大家減少考試成本，節約時間，是上班族需要獲取DP-100 考試大綱認證的最佳選擇。
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Microsoft DP-100題庫最新資訊 - 這是經過很多考生證明過的事實。
很多IT人士都想通過Microsoft DP-100題庫最新資訊 認證考試，從而在IT行業中獲取更好的提升機會，使他們的工資生活水準都有所提升。但是好多人為了通過Microsoft DP-100題庫最新資訊 認證考試花了大量時間和精力來鞏固相關知識卻沒有通過考試。這樣是很不划算。如果你選擇Goldmile-Infobiz的產品，你可以為你節約很多時間和精力來鞏固知識，但是卻可以通過Microsoft DP-100題庫最新資訊 認證考試。因為Goldmile-Infobiz的關於Microsoft DP-100題庫最新資訊 認證考試的針對性的資料可以幫助你100%通過考試。如果你考試失敗，Goldmile-Infobiz會全額退款給你。
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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