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A two-stage predictive machine learning engine that forecasts the on-time performance of flights for 15 different airports in the USA based on data collected in 2016 and 2017.

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machine-learning two-stage flight-delay-prediction pre-processing data-cleaning data-visualization airports forecasts flights feature-selection

flight_delay_prediction's Introduction

Nivedhitha D - Banner

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version :08.01.2022  View Counter  build: passing  GitHub Nivedhitha D

🤝🏻  Connect with Me

👩‍💻  About Me

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🎓  I'm a Master of Computational Data Science student at Carnegie Mellon University.
💡   I enjoy exploring new technologies, developing software solutions, and quick hacks.
🔬   I'm interested in the fields of Full Stack Data Science, Applied Machine Learning, Data Engineering and Analytics.
🌱   In my undergrad., I built two Navigation Suites, each one for two different Underwater Robots, namely, KYOGRE and ORCA!
⚡   Fun fact: I'm a textbook INTJ-A personality type, the same type as Gandalf the Grey 🦄😜👌🏻

🛠  Tech Stack

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flight_delay_prediction's Issues

[Request] source csv template

Hello Nivedhitha,

Thank you for sharing your research work, and explaining it to the Git community!

I am a PhD student in Aerospace Engineering, working at Georgia Tech (USA).
Under the scope of a System of Systems project, my team and I would like to try your promising code.
The goal is to assess the impacts of the implementation of a High Altitude Platform System (HAPS) into a flight delay model.

To do so, we would like first to run your code and understand it.
Therefore, would it be possible for you to provide the input template please?
source = f"{year}original/{year}/On_Time_On_Time_Performance{year}{month}/On_Time_On_Time_Performance{year}_{month}.csv"

Hence, we could try other data than years 2016-17, and understand the complexity and specificities of what you have developed.

We would be also very pleased to share future potential collaborations between CMU and GT.

I look forward to hearing from you.

Regards,

Thibault Ly
[email protected]

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