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NEW QUESTION: 1
What happens when an 802.11b node starts broadcasting within the range of an 802.llg access point?
A. The access point will transmit, but the node will be unable to receive.
B. Both the node and the access point will be unable to transmit.
C. The node will transmit, but the access point will be unable to receive.
D. A connection will be established,
Answer: D
NEW QUESTION: 2
Solutions Architect는 VPN 연결을 통해 온 프레미스 데이터 센터에 연결할 AWS에서 애플리케이션을 설계하고 있습니다. 솔루션은 VPN을 통해 네트워크 트래픽을 기록 할 수 있어야 합니다.
이 네트워크 트래픽을 기록하는 서비스는 무엇입니까?
A. Amazon S3 버킷 로그
B. Amazon VPC 흐름 로그
C. AWS CloudTrail 로그
D. Amazon CloudWatch Logs
Answer: B
NEW QUESTION: 3
A Security Engineer launches two Amazon EC2 instances in the same Amazon VPC but in separate Availability Zones. Each instance has a public IP address and is able to connect to external hosts on the internet. The two instances are able to communicate with each other by using their private IP addresses, but they are not able to communicate with each other when using their public IP addresses.
Which action should the Security Engineer take to allow communication over the public IP addresses?
A. Add the instance IDs to the ingress rules of the instance security groups.
B. Add the public IP addresses to the ingress rules of the instance security groups.
C. Associate the instances to the same security groups.
D. Add 0.0.0.0/0 to the egress rules of the instance security groups.
Answer: C
NEW QUESTION: 4
If you want to create a machine learning model that predicts the price of a particular stock based on its recent price history, what type of estimator should you use?
A. Unsupervised learning
B. Clustering estimator
C. Regressor
D. Classifier
Answer: C
Explanation:
Regression is the supervised learning task for modeling and predicting continuous, numeric variables. Examples include predicting real-estate prices, stock price movements, or student test scores.
Classification is the supervised learning task for modeling and predicting categorical variables. Examples include predicting employee churn, email spam, financial fraud, or student letter grades.
Clustering is an unsupervised learning task for finding natural groupings of observations (i.e. clusters) based on the inherent structure within your dataset. Examples include customer segmentation, grouping similar items in e-commerce, and social network analysis.
Reference: https://elitedatascience.com/machine-learning-algorithms
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