A company wants to use an automatic machine learning (ML) Random Cut Forest (RCF) algorithm to visualize complex real-world scenarios, such as detecting seasonality and trends, excluding outers, and imputing missing values.
The team working on this project is non-technical and is looking for an out-of-the-box solution that will require the LEAST amount of management overhead.
Which solution will meet these requirements?
A . Use an AWS Glue ML transform to create a forecast and then use Amazon QuickSight to visualize the data.
B . Use Amazon QuickSight to visualize the data and then use ML-powered forecasting to forecast the key business metrics.
C . Use a pre-build ML AMI from the AWS Marketplace to create forecasts and then use Amazon QuickSight to visualize the data.
D . Use calculated fields to create a new forecast and then use Amazon QuickSight to visualize the data.
Answer: A
Explanation:
Reference: https://aws.amazon.com/blogs/big-data/query-visualize-and-forecast-trufactor-web-session-intelligence-with-aws-data-exchange/
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