
Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.
Product Overview
Flight delays could cause airlines to incur financial losses in the form of accommodation expenses for the delayed passengers as well as penalties, fines, and operational costs for aircraft labor retention at airports. Furthermore, continual unexpected delays could cause the airline to lose their customers. This solution predicts whether a flight would be delayed at the origin airport and by how many minutes. It utilizes latent factors such as flight route, airport congestion, airline efficiency and temporal features derived from U.S. Department of Transportation's (DOT) Bureau of Transportation Statistics data on flight on-time performance for large air carriers. The solution uses tree-based models to capture and predict on-time behavior of commercial flights.
Key Data
Version | |
By | Mphasis |
Categories | |
Type | Algorithm |
Fulfillment Methods | Amazon SageMaker
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Usage Information
Training
Additional Resources
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Support Information
Flight Delay Prediction
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