Introduction to Environmental Data Science Hsieh William W. University of British Columbia Vancouver
Introduction to Environmental Data Science Hsieh William W. University of British Columbia Vancouver Statistical and machine learning methods have many applications in the environmental sciences,…
Specifikacia Introduction to Environmental Data Science Hsieh William W. University of British Columbia Vancouver
Introduction to Environmental Data Science Hsieh William W. University of British Columbia Vancouver
Statistical and machine learning methods have many applications in the environmental sciences, including prediction and data analysis in meteorology, hydrology and oceanography; pattern recognition for satellite images from remote sensing; management of agriculture and forests; assessment of climate change; and much more. It includes intuitive explanations covering the relevant background mathematics, with examples drawn from the environmental sciences. With rapid advances in machine learning in the last decade, this book provides an urgently needed, comprehensive guide to machine learning and statistics for students and researchers interested in environmental data science.
A broad range of topics is covered, including correlation, regression, classification, clustering, neural networks, random forests, boosting, kernel methods, evolutionary algorithms and deep learning, as well as the