In this project I got to work with a fun dataset. The Sentinel-2 satellite images are openly and freely accessible provided in the Earth observation program Copernicus. A group of researchers put some of them together to create novel dataset consisting out of 10 classes with in total 27,000 labeled and geo-referenced images. I used a deep learning approach, utilizing the RESNET50 architecture, to find an algorithm to classify the land use and land cover of the 64x64 pixel pictures as accurate as possible.

This dataset is all about meteorites, where they fell and when they fell! Data comes from the Meteoritical Society by way of NASA. If you want to find out more about meteorite classifications, check Wikipedia: https://en.wikipedia.org/wiki/Meteorite_classification. I created a plot and added the code here. Link to GitHub Repository Meteorites Link to GitHub Repository