Hack Airline Data with Math

Have you ever been stuck in an airport because your flight was delayed or cancelled and wondered if you could have predicted it if you'd had more data? This is your chance to find out.

DataSets:

Flight arrival and departure details for all commercial flights within the USA, from October 1987 to April 2008. This is a large dataset: there are nearly 120 million records in total, and takes up 1.6 gigabytes of space compressed and 12 gigabytes when uncompressed.

http://stat-computing.org/dataexpo/2009/

Also available:

Airlines all years 1987-2008:
https://s3.amazonaws.com/h2o-airlines-unpacked/allyears.csv (12GB)

Questions:

Predict which airport in SF Bayarea has less than 5-mins arrival delays?

Predict what are the best days/times to fly out of SFO?

Predict weather related delays based on time of day for your next return trip to SF?

https://github.com/0xdata/h2o/wiki/Hacking-Airline-DataSet-with-H2O