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Predicting Flight Delays with Deep Learning

In 2017, approximately 24% of all flights in the US were delayed by at least 15 minutes, with numbers even higher in other countries. These delays present major challenges for all areas of the American transport system, including airports, airlines, and passengers. Consequently, predicting flight delays is a problem of great interest.

Due to continuous logging of both flight data and of weather data at airports, there is an enormous amount of available data; however, predicting flight delays has historically been a difficult task due to the interconnected and sequential nature of flight delays.

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Predicting flight delays with deep learning

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