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Machine Learning on Geospatial Data with Malte Loller-Anderson & Mathilde Ørstavik

.NET Rocks!

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Navigating Geospatial Data Challenges

This chapter delves into the intricacies of working with geospatial data in machine learning, highlighting the difficulties of selecting relevant training datasets and accurately detecting structures in various environments. Emphasizing the importance of high-resolution data and innovative strategies, it discusses the ongoing need for data refinement and the incorporation of diverse categories to improve model predictions. The conversation weaves in humor while addressing the unexpected results and complexities that arise in the analysis of geospatial imagery.

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