> For the complete documentation index, see [llms.txt](https://irosyadi.gitbook.io/irosyadi/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://irosyadi.gitbook.io/irosyadi/machine-learning/ml-earth.md).

# Machine Learning for Earth Science

## AI for Earth Science

* [Dymaxionlabs](https://dymaxionlabs.com/platform/)
* [School Mapping Github by DymaxionLabs](https://github.com/dymaxionlabs/school-mapping)

## Climate

* [Climate indices](https://github.com/monocongo/climate_indices) (BSD-3-Clause) : Python implementations of various climate index algorithms which provide a geographical and temporal picture of the severity of precipitation and temperature anomalies useful for climate monitoring and research.
* [MIT Climate CoLab](https://www.climatecolab.org/) : A collaborative online community centered around a series of annual contests that seek out promising ideas for fighting climate change.
* [Climate Action Challenge](https://challenge.whatdesigncando.com) : global design competition calling on the creative community to submit bold, innovative solutions to combat the impacts of climate change.
* Improving Weather Prediction with CNN: J. A. Weyn, D. R. Durran, and R. Caruana, “Improving data-driven global weather prediction using deep convolutional neural networks on a cubed sphere,”Journal of Advances in Modeling Earth Systems, vol. 12, no. 9, Sep. 2020,ISSN: 1942-2466.doi:10.1029/2020ms002109.\[Online]. Available:<http://dx.doi.org/10.1029/2020MS002109>. Code: <https://github.com/jweyn/DLWP-CS>