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Predicting Sea Ice Velocity using Neural Networks and XGBoost
Predicting the velocity of sea ice drift in the Arctic
Enabling a Sustainable Marketplace with AI
This challenge gave us the opportunity to quickly compile a model that could predict sea-ice movement. We were proud of being able to contribute to the making a difference with climate change.
See CO2, like never before.
The wondrous whimsical world of polar ice drift!
"C the CO2" ~ A visualization of CO2 emissions per city: as a city!
Reducing CO2 Challenge. Visualizing cities' carbon emission data!
A global leaderboard of cities' CO2 emissions. Find our how your city ranks!
beep boop creativity
Predicting the impact of changing hydrological patterns on the frequency and duration of sewage overflows
The objective of this challenge is to improve the resolution of weather forecasts using machine learning. #challenge-super-resolution
Wind Energy Prediction
#challenge-sea-ice
Using weather data to determine bee honey production
With the myriad of problems arising due to climate change, our team seeks visualize how recent changes to climate have affected pollinator species, and what this means for our future.
Predictive model of honey production using climate data
Terraforming Earth
Providing insightful visualisations for sea ice motion in the Arctic
