CRC Press Large-Scale Machine Learning in Earth Sciences - Data Mining

This comprehensive guide explores the intersection of machine learning and Earth sciences, offering practical insights into applying large-scale data mining techniques to environmental challenges. Edited by Ashok Srivastava, Ramakrishna Nemani, and Karsten Steinhaeuser, the book addresses both the opportunities and challenges facing the machine learning community when analysing Earth science datasets to tackle pressing societal questions. Part of the Chapman & Hall/CRC Data Mining and Knowledge Discovery Series, this resource bridges the gap between computational methods and environmental applications, providing computer scientists and researchers with essential knowledge for developing solutions to real-world environmental problems. The book combines theoretical foundations with practical applications, making it valuable for professionals seeking to understand how machine learning can drive innovation in analysing planetary systems and supporting climate-related decision-making.