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NEW QUESTION: 1
Predictive Power, Prediction Confidence and Model Graphs On the model graph plot:
Note: There are 2 correct answers to this question.
A. Of the validation dataset of the perfect model and that of the random model". As the curve of the generated model approaches the curve of the perfect model, the value of the predictive power approaches 1.
B. Of the training and validation datasets the training dataset and that of the validation dataset "divided by "the area found between the curve of the perfect model and that of the random model"
C. Produce deep analysis of the data using different visualization
techniques, such as scatter matrix charts, parallel coordinates, cluster charts, and decision trees.
Answer: A,B

NEW QUESTION: 2
A company that provides wireless services needs a solution to store and analyze log files about user activities.
Currently, log files are delivered daily to Amazon Linux on Amazon EC2 instance. A batch script is run once a day to aggregate data used for analysis by a third-party tool. The data pushed to the third-party tool is used to generate a visualization for end users. The batch script is cumbersome to maintain, and it takes several hours to deliver the ever-increasing data volumes to the third-party tool. The company wants to lower costs, and is open to considering a new tool that minimizes development effort and lowers administrative overhead. The company wants to build a more agile solution that can store and perform the analysis in near-real time, with minimal overhead. The solution needs to be cost effective and scalable to meet the company's end-user base growth.
Which solution meets the company's requirements?
A. Use an Amazon Kinesis agent running on an EC2 instance in an Auto Scaling group to collect and send the data to an Amazon Kinesis Data Forehose delivery stream. The Kinesis Data Firehose delivery stream will deliver the data directly to Amazon ES. Use Kibana to visualize the data.
B. Use an Amazon Kinesis agent running on an EC2 instance to collect and send the data to an Amazon Kinesis Data Firehose delivery stream. The Kinesis Data Firehose delivery stream will deliver the data to Amazon S3. Use an AWS Lambda function to deliver the data from Amazon S3 to Amazon ES. Use Kibana to visualize the data.
C. Use an in-memory caching application running on an Amazon EBS-optimized EC2 instance to capture the log data in near real-time. Install an Amazon ES cluster on the same EC2 instance to store the log files as they are delivered to Amazon EC2 in near real-time. Install a Kibana plugin to create the visualizations.
D. Develop a Python script to failure the data from Amazon EC2 in real time and store the data in Amazon S3. Use a copy command to copy data from Amazon S3 to Amazon Redshift. Connect a business intelligence tool running on Amazon EC2 to Amazon Redshift and create the visualizations.
Answer: A
Explanation:
Explanation
https://docs.aws.amazon.com/firehose/latest/dev/writing-with-agents.html

NEW QUESTION: 3
일반적으로 응용 프로그램에서 결과를 처리하기 전에 요청에서 오류가 생성되었는지 여부를 확인해야 합니다. 오류가 발생했는지 확인하는 가장 쉬운 방법은 Amazon RDS API의 응답에서 _____________ 노드를 찾는 것입니다.
A. 오류
B. 잘못된
C. 거짓
Answer: A

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