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NEW QUESTION: 1
次の表に示すサブネットを含むVNET1という名前の仮想ネットワークがあります。
Training H13-211_V3.0 For Exam
次の表に示すネットワーク構成を持つ2つのAzure仮想マシンがあります。
Training H13-211_V3.0 For Exam
NSG1の場合、次の表に示すインバウンドセキュリティルールを作成します。
Training H13-211_V3.0 For Exam
NSG2の場合、次の表に示すインバウンドセキュリティルールを作成します。
Training H13-211_V3.0 For Exam
次の各ステートメントについて、ステートメントがtrueの場合は[はい]を選択します。それ以外の場合は、[いいえ]を選択します。
注:それぞれの正しい選択は1ポイントの価値があります。
Training H13-211_V3.0 For Exam
Answer:
Explanation:
Training H13-211_V3.0 For Exam
Explanation:
Box 1: Yes
The inbound security rule for NSG1 allows TCP port 1433 from 10.10.2.0/24 (or Subnet2 where VM2 and VM3
are located) to 10.10.1.0/24 (or Subnet1 where VM1 is located) while the inbound security rule for NSG2
blocks TCP port 1433 from 10.10.2.5 (or VM2) to 10.10.1.5 (or VM1). However, the NSG1 rule has a higher
priority (or lower value) than the NSG2 rule.
Box 2: Yes
No rule explicitly blocks communication from VM1. The default rules, which allow communication, are thus
applied.
Box 3: Yes
No rule explicitly blocks communication between VM2 and VM3 which are both on Subnet2. The default rules,
which allow communication, are thus applied.
Reference:
https://docs.microsoft.com/en-us/azure/virtual-network/security-overview

NEW QUESTION: 2
Consider this requirement for a business transaction:
If approved, the request is forwarded to the Fulfilment department
If the manager rejects the request, it is sent back to the employee for reconciliation or cancellation The Fulfillment department will process the request if the requested items are in stock An employee submits a request to purchase equipment. The request is sent to the manager for review and approval.
Select the case life cycle design that most closely follows the guidelines for identifying and naming stages.
Training H13-211_V3.0 For Exam
A. Option A
B. Option B
C. Option C
D. Option D
Answer: D

NEW QUESTION: 3
Azure Machine Learning Studioの2クラスニューラルネットワークモジュールを使用して、バイナリ分類モデルを構築します。 Tune Model Hyperparametersモジュールを使用して、モデルの精度を調整します。
Tune Model Hyperparametersモジュールを使用して、調整する必要があるハイパーパラメーターを選択する必要があります。
どの2つのハイパーパラメーターを使用する必要がありますか?それぞれの正解はソリューションの一部を示しています。
注:それぞれの正しい選択には1ポイントの価値があります。
A. Learning Rate
B. Number of learning iterations
C. Hidden layer specification
D. Number of hidden nodes
E. The type of the normalizer
Answer: B,C
Explanation:
Explanation
D: For Number of learning iterations, specify the maximum number of times the algorithm should process the training cases.
E: For Hidden layer specification, select the type of network architecture to create.
Between the input and output layers you can insert multiple hidden layers. Most predictive tasks can be accomplished easily with only one or a few hidden layers.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/two-class-neural-network