Isbn: 9783032114259 - application of machine learning in earth sciences: a practical approach (7 risultati)

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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces the reader to applications of machine learning (ML) in Earth Sciences. In detail, it describes the basic application of machine learning algorithms and models and their potential in Earth Sciences. It discusses the use of several tools and software and the typical workflow for ML applications in Earth Sciences. This book provides a comparative analysis of how standard processes and ML algorithms work in several Earth Sciences applications. Case studies from the various fields of Earth Sciences are presented to illustrate how to apply ML and Deep Learning, these include regression, forecasting, time series analysis in Climate studies, classification methods using multi-spectral data clustering, and dimensionality reduction in classification. This book reviews ML/AI models, algorithms, and methods, analyse case studies, and examine methods of application of ML/AI techniques to specific areas of Earth Sciences. It aims to serve all professionals, and researchers, scientists alike in academics, industries, government, and beyond.…

Hardcover. Condizione: Brand New. 676 pages. 6.14x1.44x9.21 inches. In Stock.

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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book introduces the reader to applications of machine learning (ML) in Earth Sciences. In detail, it describes the basic application of machine learning algorithms and models and their potential in Earth Sciences. It discusses the use of several tools and software and the typical workflow for ML applications in Earth Sciences. This book provides a comparative analysis of how standard processes and ML algorithms work in several Earth Sciences applications. Case studies from the various fields of Earth Sciences are presented to illustrate how to apply ML and Deep Learning, these include regression, forecasting, time series analysis in Climate studies, classification methods using multi-spectral data clustering, and dimensionality reduction in classification. This book reviews ML/AI models, algorithms, and methods, analyse case studies, and examine methods of application of ML/AI techniques to specific areas of Earth Sciences. It aims to serve all professionals, and researchers, scientists alike in academics, industries, government, and beyond. 665 pp. Englisch.…

Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book introduces the reader to applications of machine learning (ML) in Earth Sciences. In detail, it describes the basic application of machine learning algorithms and models and their potential in Earth Sciences. It discusses the use of several tools and software and the typical workflow for ML applications in Earth Sciences. This book provides a comparative analysis of how standard processes and ML algorithms work in several Earth Sciences applications. Case studies from the various fields of Earth Sciences are presented to illustrate how to apply ML and Deep Learning, these include regression, forecasting, time series analysis in Climate studies, classification methods using multi-spectral data clustering, and dimensionality reduction in classification. This book reviews ML/AI models, algorithms, and methods, analyse case studies, and examine methods of application of ML/AI techniques to specific areas of Earth Sciences. It aims to serve all professionals, and researchers, scientists alike in academics, industries, government, and beyond.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 680 pp. Englisch.…

Hardcover. Condizione: new. Hardcover. This book introduces the reader to applications of machine learning (ML) in Earth Sciences. In detail, it describes the basic application of machine learning algorithms and models and their potential in Earth Sciences. It discusses the use of several tools and software and the typical workflow for ML applications in Earth Sciences. This book provides a comparative analysis of how standard processes and ML algorithms work in several Earth Sciences applications. Case studies from the various fields of Earth Sciences are presented to illustrate how to apply ML and Deep Learning, these include regression, forecasting, time series analysis in Climate studies, classification methods using multi-spectral data clustering, and dimensionality reduction in classification. This book reviews ML/AI models, algorithms, and methods, analyse case studies, and examine methods of application of ML/AI techniques to specific areas of Earth Sciences. It aims to serve all professionals, and researchers, scientists alike in academics, industries, government, and beyond. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…