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NEW QUESTION: 1
An application currently resides on an on-premises virtual machine that has 2 CPU cores, 4 GB of RAM, 20 GB of hard disk space, and a 10 megabit/second network connection.
You plan to migrate the application to Azure. You have the following requirements:
- You must not make changes to the application.
- You must minimize the costs for hosting the application.
You need to recommend the appropriate virtual machine instance type.
Which virtual machine tier should you recommend?
A. Optimized Compute (D Series)
B. General Purpose Compute, Standard Tier (A Series)
C. General Purpose Compute, Basic Tier (A Series)
D. Network Optimized (A Series)
Answer: C
Explanation:
Ref: http://azure.microsoft.com/en-us/pricing/details/virtual-machines/

NEW QUESTION: 2
ネットワークにcontoso.comという名前のActive Directoryドメインが含まれています。 ドメインには、Windows Server 2016を実行するServer1とServer2という名前の2つのサーバーが含まれています。
Server1にIPアドレス管理（IPAM）がインストールされています。 Server2には、Microsoft System Center 2016のVirtual Machine Manager（VMM）がインストールされています。
IPAMとVMMを統合する必要があります。
各サーバーにどのタイプのオブジェクトを作成する必要がありますか。 回答するには、適切なオブジェクトタイプを正しいサーバーにドラッグします。 各オブジェクトタイプは、1回、複数回、またはまったく使用しないことができます。 コンテンツを表示するには、ペイン間の分割バーをドラッグするか、スクロールする必要があります。

Answer:
Explanation:

Explanation:
References:
https://technet.microsoft.com/en-us/library/dn783349(v=ws.11).aspx

NEW QUESTION: 3
You are building an experiment using the Azure Machine Learning designer.
You split a dataset into training and testing sets. You select the Two-Class Boosted Decision Tree as the algorithm.
You need to determine the Area Under the Curve (AUC) of the model.
Which three modules should you use in sequence? To answer, move the appropriate modules from the list of modules to the answer area and arrange them in the correct order.

Answer:
Explanation:

Explanation:
Step 1: Train Model
Two-Class Boosted Decision Tree
First, set up the boosted decision tree model.
1. Find the Two-Class Boosted Decision Tree module in the module palette and drag it onto the canvas.
2. Find the Train Model module, drag it onto the canvas, and then connect the output of the Two-Class Boosted Decision Tree module to the left input port of the Train Model module.
The Two-Class Boosted Decision Tree module initializes the generic model, and Train Model uses training data to train the model.
3. Connect the left output of the left Execute R Script module to the right input port of the Train Model module (in this tutorial you used the data coming from the left side of the Split Data module for training).
This portion of the experiment now looks something like this:

Step 2: Score Model
Score and evaluate the models
You use the testing data that was separated out by the Split Data module to score our trained models. You can then compare the results of the two models to see which generated better results.
Add the Score Model modules
1. Find the Score Model module and drag it onto the canvas.
2. Connect the Train Model module that's connected to the Two-Class Boosted Decision Tree module to the left input port of the Score Model module.
3. Connect the right Execute R Script module (our testing data) to the right input port of the Score Model module.

Step 3: Evaluate Model
To evaluate the two scoring results and compare them, you use an Evaluate Model module.
1. Find the Evaluate Model module and drag it onto the canvas.
2. Connect the output port of the Score Model module associated with the boosted decision tree model to the left input port of the Evaluate Model module.
3. Connect the other Score Model module to the right input port.

NEW QUESTION: 4
Which three rules apply when configuring agent teams? (Choose three.)
A. An agent team can have only one primary supervisor.
B. An agent can be a member of only one agent team.
C. An agent can be a member of multiple agent teams.
D. An agent team can have multiple primary supervisors but can only be a member of one teams.
E. All agents that belong to an agent team and all supervisors for that agent team can be on multiple peripherals.
F. All agents that belong to an agent team and all supervisors for that agent team must be on the same peripheral.
G. An agent team can have only one primary supervisor but can be a member of multiple teams.
H. An agent team can have multiple primary supervisors.
Answer: A,B,F