Machine Learning in Earth, Environmental and Planetary Sciences Theoretical and Practical Applications
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Form:Einzelkauf Download
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Sprache:Englisch
Fr. 137.90
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
ePUB 3
Kopierschutz
Nein
Family Sharing
Nein
Text-to-Speech
Ja
Erscheinungsdatum
03.07.2023
Verlag
Elsevier Science & Techn.Seitenzahl
250 (Printausgabe)
Dateigröße
76476 KB
Sprache
Englisch
EAN
9780443152856
Machine Learning in Earth, Environmental and Planetary Sciences: Theoretical and Practical Applications is a practical guide on implementing different variety of extreme learning machine algorithms to Earth and environmental data. The book provides guided examples using real-world data for numerous novel and mathematically detailed machine learning techniques that can be applied in Earth, environmental, and planetary sciences, including detailed MATLAB coding coupled with line-by-line descriptions of the advantages and limitations of each method. The book also presents common postprocessing techniques required for correct data interpretation.
This book provides students, academics, and researchers with detailed understanding of how machine learning algorithms can be applied to solve real case problems, how to prepare data, and how to interpret the results.
- Describes how to develop different schemes of machine learning techniques and apply to Earth, environmental and planetary data
- Provides detailed, guided line-by-line examples using real-world data, including the appropriate MATLAB codes
- Includes numerous figures, illustrations and tables to help readers better understand the concepts covered
This book provides students, academics, and researchers with detailed understanding of how machine learning algorithms can be applied to solve real case problems, how to prepare data, and how to interpret the results.
- Describes how to develop different schemes of machine learning techniques and apply to Earth, environmental and planetary data
- Provides detailed, guided line-by-line examples using real-world data, including the appropriate MATLAB codes
- Includes numerous figures, illustrations and tables to help readers better understand the concepts covered
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