case study:
'climatewins'
Join me on a journey with ClimateWins,
a European nonprofit organization dedicated to combating climate change.
(CF student case study)
*updated as of Jun. 7th, 2024*
As their data analyst, I'll lead the charge in integrating machine learning to forecast climate consequences, empowering ClimateWins to address extreme weather events with cutting-edge algorithms such as Gradient Descent, K-Nearest Neighbors (KNN), Decision Trees, and Artificial Neural Networks (ANN) with Python to derive a data-driven strategy.
Here are the questions they want me to answer first:
1. How is machine learning used? Is it applicable to weather data?
2. ClimateWins has heard of ethical concerns surrounding machine learning and AI. Are there any concerns specific to this project?
3. Historically, what have the maximums and minimums in temperature been?
4. Can machine learning be used to predict whether weather conditions will be favorable on a certain day? (If so, it could also be possible to predict danger.)
I'll delve into these critical questions, exploring the intersection of machine learning and weather data to drive ClimateWins forward. Together, we'll address ethical considerations, uncover historical temperature trends, and pave the way for predicting weather conditions with unprecedented accuracy, shaping a safer and more resilient future for all.
Follow along to view the results:
climatewins-proposal-strategy-presentation from kgdata on Vimeo.
climatewins-video-presentation-kg from kgdata on Vimeo.
Join me on a journey with ClimateWins, a European nonprofit organization dedicated to combating climate change where I'll answer pertinent questions, such as, can machine learning be used to predict whether weather conditions will be favorable on a certain day?
Thanks for viewing!