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Tom Hengl: “Modern challanges of geospatial data science: the Open-Earth-Monitor project” Ben Graeler: “AI Strategy for Earth System Data – KI:STE project” Martin Schultz: “Machine learning for weather, air quality and climate” Markus Konkol: “Open Reproducible Research – Concepts, challenges, and solutions” Jakub Nowosad: “Geocomputation with R’s guide to reproducible spatial data analysis” Edzer Pebesma: “R-spatial updates: sf, sftime, stars” Christian Autermann: “GeoNode as Research Data Infrastructure” Martijn Visser; Maarten Pronk: “JuliaGeo: a gentle introduction” Martin Fleischmann: “Introduction to GeoPandas and its Python ecosystem” Krzystof Dyba: “Benchmarking R and Python for spatial data processing” Ben Graeler: “Extreme events session” Leandro Parente: “Accessing and using data cubes: spatial overlay, visualization and modeling – Python tutorial” Markus Abel: “Stochastic processes, analysis, examples (Python tutorial)” Edzer Pebesma & Leandro Parente: “Geo-arrow and geo-parquet” Ribana Roscher: “Explainable ML” Patrick Schratz: “Introduction to mlr3 (R tutorial)” and Patrick Schratz & Leandro Parente: “Spatial modeling using mlr3 (R tutorial)” Hanna Meyer: “ML in R: how to deal with extrapolation and overfitting problems” Tim Appelhans: “Visualization cloud-optimized (large) datasets in R (R tutorial)”
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