This hands-on tutorial explores two distinct machine learning projects centered around geospatial data analysis. It aims to shed light on the unique challenges encountered when working with geospatial data and provides practical insights into evaluating and scoring geospatial models.
While not intended as an introductory course to machine learning or an exploration of cutting-edge techniques like Transformer models, this tutorial offers valuable depth into geospatial data processing and modeling. Proficiency in the scientific Python stack, encompassing tools such as NumPy, Pandas, and Xarray, is advantageous, though not obligatory for participation. Participants can expect a hands-on approach, engaging with real-world earth systems science geospatial datasets.
Create a custom schedule.
Take it with you on mobile.
Get listed in the directory.
