P.S. VCESoft在Google Drive上分享了免費的、最新的DP-100考試題庫：https://drive.google.com/open?id=1aY3BcIl6Ps3dACC6shUUAli-zuTTVQni
競爭頗似打網球，與球藝勝過你的對手比賽，可以提高你的水準。你可以選擇參加最近很有人氣的 Microsoft 的 DP-100 認證考試。得到這個考試的認證資格，你可以得到很大的好處。如果你要參加 DP-100 認證考試，Microsoft 的 DP-100 考古題是你最好的準備工具。這個資料可以幫助你輕鬆地通過考試。這是一個評價很高的資料，有了它，你就不用再擔心你的考試了。
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Optimize language models for AI applications | 25-30% | - Optimize with Retrieval Augmented Generation
|
| Topic 2: Explore data and run experiments | 20-25% | - Run experiments
|
| Topic 3: Train and deploy models | 25-30% | - Train models
|
| Topic 4: Design and prepare a machine learning solution | 20-25% | - Design a machine learning solution
|
VCESoft是唯一能供給你們需求的全部的Microsoft DP-100 認證考試相關資料的網站。利用VCESoft提供的資料通過Microsoft DP-100 認證考試是不成問題的，而且你可以以很高的分數通過考試得到相關認證。
問題 #369
You arc I mating a deep learning model to identify cats and dogs. You have 25,000 color images.
You must meet the following requirements:
* Reduce the number of training epochs.
* Reduce the size of the neural network.
* Reduce over-fitting of the neural network.
You need to select the image modification values.
Which value should you use? To answer, select the appropriate Options in the answer area.
NOTE: Each correct selection is worth one point.
答案：
解題說明：
問題 #370
You are performing feature engineering on a dataset.
You must add a feature named CityName and populate the column value with the text London.
You need to add the new feature to the dataset.
Which Azure Machine Learning Studio module should you use?
答案：A
解題說明：
Typical metadata changes might include marking columns as features.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/edit-metadata
問題 #371
You manage an Azure Machine Learning workspace by using the Python SDK v2.
You must create a compute cluster in the workspace. The compute cluster must run workloads and properly handle interruptions. You start by calculating the maximum amount of compute resources required by the workloads and size the cluster to match the calculations.
The cluster definition includes the following properties and values:
* name="mlcluster1''
* size="STANDARD.DS3.v2"
* min_instances=1
* maxjnstances=4
* tier="dedicated"
The cost of the compute resources must be minimized when a workload is active Of idle. Cluster property changes must not affect the maximum amount of compute resources available to the workloads run on the cluster.
You need to modify the cluster properties to minimize the cost of compute resources.
Which properties should you modify? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
答案：
解題說明：
問題 #372
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.
答案：
解題說明：
Explanation:
Scenario:
Experiments for local crowd sentiment models must combine local penalty detection data.
Crowd sentiment models must identify known sounds such as cheers and known catch phrases. Individual crowd sentiment models will detect similar sounds.
Note: Evaluate the changed in correlation between model error rate and centroid distance In machine learning, a nearest centroid classifier or nearest prototype classifier is a classification model that assigns to observations the label of the class of training samples whose mean (centroid) is closest to the observation.
References:
https://en.wikipedia.org/wiki/Nearest_centroid_classifier
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/sweep-clustering
問題 #373
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.
答案：
解題說明：
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/
問題 #374
......
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DP-100題庫分享: https://www.vcesoft.com/DP-100-pdf.html
從Google Drive中免費下載最新的VCESoft DP-100 PDF版考試題庫：https://drive.google.com/open?id=1aY3BcIl6Ps3dACC6shUUAli-zuTTVQni