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"C the CO2" ~ A visualization of CO2 emissions per city: as a city!
The objective of this challenge is to improve the resolution of weather forecasts using machine learning. #challenge-super-resolution
A global leaderboard of cities' CO2 emissions. Find our how your city ranks!
Predicting the velocity of sea ice drift in the Arctic
Providing better information for short-term predictions on wind power production
Predictive model of honey production using climate data
Providing insightful visualisations for sea ice motion in the Arctic
Visualisation of urban GHG emission - Work in Progress :D
Analyze smart building data to predict energy saving
Enabling a Sustainable Marketplace with AI
Interactive web visualisation comparing missions and trends across global cities.
beep boop creativity
Using weather data to determine bee honey production
SRGAN with LSTM to make Super resolution by keeping the time information on temperature change
Wind energy prediction
Predicting Sea Ice Velocity using Neural Networks and XGBoost
The wondrous whimsical world of polar ice drift!
Predicting the impact of changing hydrological patterns on the frequency and duration of sewage overflows
Reducing CO2 Challenge.
Visualizing cities' carbon emission data!
Wind Energy Prediction
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.
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