Explainable Machine Learning for Geospatial Data Analysis A DataCentric Approach The book "Explainable Machine Learning for Geospatial Data Analysis A DataCentric Approach" by Dr. Suresh Venkatasubramanian and Dr. Jesse Berry is a comprehensive guide to understanding the principles and practices of explainable machine learning in the context of geospatial data analysis. The authors present a novel approach to machine learning that emphasizes the importance of interpreting and explaining the results of machine learning algorithms, particularly in the field of geospatial data analysis. The book provides a detailed overview of the current state of the art in machine learning techniques and their applications in geospatial data analysis, highlighting the challenges and limitations of traditional machine learning approaches. It also offers practical solutions to address these challenges and provide more accurate and reliable results. The book begins with an introduction to the basics of machine learning and its applications in geospatial data analysis, followed by an overview of the current state of the art in machine learning techniques and their limitations. The authors then delve into the concept of explainability and its importance in ensuring trustworthy and reliable results from machine learning models.

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