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NEW QUESTION: 1
Amazon EC2 인스턴스의 트래픽 흐름을 모니터링하라는 요청을 받았습니다. 비정형 패턴을 찾아 깊은 패킷 검사를 수행하게 됩니다.
어떤 도구를 사용하여 이 데이터를 볼 수 있습니까?
A. VPC 흐름 로그
B. CloudWatch 로그
C. Wireshark
D. AWS CLI
Answer: C
Explanation:
https://www.slideshare.net/TeriRadichel/packet-capture-on-aws

NEW QUESTION: 2
誰も、スクラムマスターでさえも、開発チームに製品のビルド方法を教えていません。
A. 真
B. 偽
Answer: A

NEW QUESTION: 3
Refer to the exhibit.

Users are reporting that inbound calls from the PSTN are dropping when not answered within 10 seconds. Calls come in via ISDN T1 PRI. Which configuration change is needed to prevent the calls from dropping?
A. Remove the timeouts wait-release 10 command from under the voice-port.
B. Remove the timer receive-rtcp 2 command from under the gateway.
C. Remove the timer receive-rtp 10000 command from under the gateway.
D. Remove the timeouts initial 10 command from under the voice-port.
E. Modify the Call Forward No Answer setting in CUCM to redirect calls to Voicemail or another extension.
Answer: B

NEW QUESTION: 4
You need to correct the model fit issue.
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:

Explanation:
Step 1: Augment the data
Scenario: Columns in each dataset contain missing and null values. The datasets also contain many outliers.
Step 2: Add the Bayesian Linear Regression module.
Scenario: You produce a regression model to predict property prices by using the Linear Regression and Bayesian Linear Regression modules.
Step 3: Configure the regularization weight.
Regularization typically is used to avoid overfitting. For example, in L2 regularization weight, type the value to use as the weight for L2 regularization. We recommend that you use a non-zero value to avoid overfitting.
Scenario:
Model fit: The model shows signs of overfitting. You need to produce a more refined regression model that reduces the overfitting.
Incorrect Answers:
Multiclass Decision Jungle module:
Decision jungles are a recent extension to decision forests. A decision jungle consists of an ensemble of decision directed acyclic graphs (DAGs).
L-BFGS:
L-BFGS stands for "limited memory Broyden-Fletcher-Goldfarb-Shanno". It can be found in the wwo-Class Logistic Regression module, which is used to create a logistic regression model that can be used to predict two (and only two) outcomes.
References:
<https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regr ession>