Explainable Machine Learning for Geospatial Data Analysis A Data-Centric Approach


Free Download Explainable Machine Learning for Geospatial Analysis: A Data-Centric Approach by Courage Kamusoko
English | 6, | ISBN: 1032503807 | 266 pages | MOBI | 9.89 Mb
Explainable machine learning (XML), a subfield of AI, is focused on making complex AI understandable to humans. This book highlights and explains the details of machine learning models used in geospatial data analysis. It demonstrates the need for a data-centric, explainable machine learning approach to obtain new insights from geospatial data. It presents the opportunities, , and gaps in the machine and deep learning approaches for geospatial data analysis and how they are applied to solve various environmental problems in land cover changes and in modeling forest canopy height and aboveground biomass density. The author also includes guidelines and scripts (R, ) valuable for readers.
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Data Governance A Guide


Free Download : A Guide by Dimitrios Sargiotis
English | September 12, | ISBN: 3031672674 | 572 pages | MOBI | 14 Mb
This book is a resource designed to demystify the complex world of data governance for professionals across various sectors. This guide provides in-depth insights, methodologies, and best to help organizations manage their data effectively and securely. It covers topics such as data quality, privacy, security, and ensuring that readers gain a holistic understanding of how to establish and maintain a robust data governance framework. Through a blend of knowledge and applications, this book addresses the and benefits of data governance, equipping readers with the tools needed to navigate the evolving data landscape.
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