Machine Learning for Planetary Science

Written By Joern Helbert
Machine Learning for Planetary Science
  • Publsiher : Elsevier
  • Release : 01 March 2021
  • ISBN : 0128187220
  • Pages : 400 pages
  • Rating : 4/5 from 21 reviews
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Read or download book entitled Machine Learning for Planetary Science written by Joern Helbert which was release on 01 March 2021, this book published by Elsevier. Available in PDF, EPUB and Kindle Format. Book excerpt: Machine Learning for Planetary Science presents planetary scientists with a way to introduce machine learning into the research workflow as increasingly large nonlinear datasets are acquired from planetary exploration missions. The book explores research that leverages machine learning methods to enhance our scientific understanding of planetary data and serves as a guide for selecting the right methods and tools for solving a variety of everyday problems in planetary science using machine learning. Illustrating ways to employ machine learning in practice with case studies, the book is clearly organized into four parts to provide thorough context and easy navigation. The book covers a range of issues, from data analysis on the ground to data analysis onboard a spacecraft, and from prioritization of novel or interesting observations to enhanced missions planning. This book is therefore a key resource for planetary scientists working in data analysis, missions planning, and scientific observation. Includes links to a code repository for sharing codes and examples, some of which include executable Jupyter notebook files that can serve as tutorials Presents methods applicable to everyday problems faced by planetary scientists and sufficient for analyzing large datasets Serves as a guide for selecting the right method and tools for applying machine learning to particular analysis problems Utilizes case studies to illustrate how machine learning methods can be employed in practice

Machine Learning for Planetary Science

Machine Learning for Planetary Science
  • Author : Joern Helbert,Mario D'Amore,Michael Aye,Hannah Kerner
  • Publisher : Elsevier
  • Release Date : 2021-03-01
  • Total pages : 400
  • ISBN : 0128187220
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Summary : Machine Learning for Planetary Science presents planetary scientists with a way to introduce machine learning into the research workflow as increasingly large nonlinear datasets are acquired from planetary exploration missions. The book explores research that leverages machine learning methods to enhance our scientific understanding of planetary data and serves as ...

Machine Learning and Artificial Intelligence in Geosciences

Machine Learning and Artificial Intelligence in Geosciences
  • Author : Anonim
  • Publisher : Academic Press
  • Release Date : 2020-09-25
  • Total pages : 316
  • ISBN : 0128187220
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Summary : Advances in Geophysics, Volume 61 - Machine Learning and Artificial Intelligence in Geosciences, the latest release in this highly-respected publication in the field of geophysics, contains new chapters on a variety of topics, including a historical review on the development of machine learning, machine learning to investigate fault rupture on various ...

Deep learning for the Earth Sciences

Deep learning for the Earth Sciences
  • Author : Gustau Camps-Valls,Devis Tuia,Xiao Xiang Zhu,Markus Reichstein
  • Publisher : John Wiley & Sons
  • Release Date : 2021-09-27
  • Total pages : 432
  • ISBN : 0128187220
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Summary : Explore this insightful treatment of deep learning in the field of earth sciences, from four leading voices in the field Deep learning is a fundamental technique in modern artificial intelligence and is being applied to disciplines across the scientific spectrum. Earth science is no exception. Yet, the link between deep ...

Machine Learning Techniques for Space Weather

Machine Learning Techniques for Space Weather
  • Author : Enrico Camporeale,Simon Wing,Jay Johnson
  • Publisher : Unknown
  • Release Date : 2018-06
  • Total pages : 400
  • ISBN : 0128187220
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Summary : Machine Learning Techniques for Space Weather provides a thorough and accessible presentation of machine learning techniques that can be employed by space weather professionals. Additionally, it presents an overview of real-world applications in space science to the machine learning community, offering a bridge between the fields. As this volume demonstrates, ...

Large Scale Machine Learning in the Earth Sciences

Large Scale Machine Learning in the Earth Sciences
  • Author : Ashok N. Srivastava,Ramakrishna Nemani,Karsten Steinhaeuser
  • Publisher : CRC Press
  • Release Date : 2017-08-01
  • Total pages : 208
  • ISBN : 0128187220
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Summary : From the Foreword: "While large-scale machine learning and data mining have greatly impacted a range of commercial applications, their use in the field of Earth sciences is still in the early stages. This book, edited by Ashok Srivastava, Ramakrishna Nemani, and Karsten Steinhaeuser, serves as an outstanding resource for anyone ...

Knowledge Discovery in Big Data from Astronomy and Earth Observation

Knowledge Discovery in Big Data from Astronomy and Earth Observation
  • Author : Petr Skoda,Fathalrahman Adam
  • Publisher : Elsevier
  • Release Date : 2020-04-10
  • Total pages : 472
  • ISBN : 0128187220
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Summary : Knowledge Discovery in Big Data from Astronomy and Earth Observation: Astrogeoinformatics bridges the gap between astronomy and geoscience in the context of applications, techniques and key principles of big data. Machine learning and parallel computing are increasingly becoming cross-disciplinary as the phenomena of Big Data is becoming common place. This ...

Machine Learning Methods in the Environmental Sciences

Machine Learning Methods in the Environmental Sciences
  • Author : William W. Hsieh
  • Publisher : Cambridge University Press
  • Release Date : 2009-07-30
  • Total pages : 349
  • ISBN : 0128187220
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Summary : A graduate textbook that provides a unified treatment of machine learning methods and their applications in the environmental sciences....

Large Scale Machine Learning in the Earth Sciences

Large Scale Machine Learning in the Earth Sciences
  • Author : Ashok N. Srivastava,Ramakrishna Nemani,Karsten Steinhaeuser
  • Publisher : CRC Press
  • Release Date : 2017-08-01
  • Total pages : 208
  • ISBN : 0128187220
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Summary : From the Foreword: "While large-scale machine learning and data mining have greatly impacted a range of commercial applications, their use in the field of Earth sciences is still in the early stages. This book, edited by Ashok Srivastava, Ramakrishna Nemani, and Karsten Steinhaeuser, serves as an outstanding resource for anyone ...

Machine Learning on Mars

Machine Learning on Mars
  • Author : Hannah Rae Kerner
  • Publisher : Unknown
  • Release Date : 2019
  • Total pages : 269
  • ISBN : 0128187220
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Summary : There are more than 20 active missions exploring planets and small bodies beyond Earth in our solar system today. Many more have completed their journeys or will soon begin. Each spacecraft has a suite of instruments and sensors that provide a treasure trove of data that scientists use to advance our ...

Machine Learning for Decision Makers

Machine Learning for Decision Makers
  • Author : Patanjali Kashyap
  • Publisher : Apress
  • Release Date : 2018-01-04
  • Total pages : 355
  • ISBN : 0128187220
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Summary : Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Decision Makers serves as an excellent resource for establishing the ...

Overcoming Data Scarcity in Earth Science

Overcoming Data Scarcity in Earth Science
  • Author : Angela Gorgoglione,Alberto Castro Casales,Christian Chreties Ceriani,Lorena Etcheverry Venturini
  • Publisher : MDPI
  • Release Date : 2020-05-22
  • Total pages : 94
  • ISBN : 0128187220
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Summary : heavily Environmental mathematical models represent one of the key aids for scientists to forecast, create, and evaluate complex scenarios. These models rely on the data collected by direct field observations. However, assembly of a functional and comprehensive dataset for any environmental variable is difficult, mainly because of i) the high ...

Machine Learning

Machine Learning
  • Author : Yagang Zhang
  • Publisher : BoD – Books on Demand
  • Release Date : 2010-02-01
  • Total pages : 446
  • ISBN : 0128187220
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Summary : Machine learning techniques have the potential of alleviating the complexity of knowledge acquisition. This book presents today’s state and development tendencies of machine learning. It is a multi-author book. Taking into account the large amount of knowledge about machine learning and practice presented in the book, it is divided ...

Machine Learning Optimization and Data Science

Machine Learning  Optimization  and Data Science
  • Author : Giuseppe Nicosia
  • Publisher : Springer Nature
  • Release Date : 2021-08-04
  • Total pages : 212
  • ISBN : 0128187220
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Summary : Download or read online Machine Learning Optimization and Data Science written by Giuseppe Nicosia, published by Springer Nature which was released on . Get Machine Learning Optimization and Data Science Books now! Available in PDF, ePub and Kindle....

Advances in Machine Learning and Data Mining for Astronomy

Advances in Machine Learning and Data Mining for Astronomy
  • Author : Michael J. Way,Jeffrey D. Scargle,Kamal M. Ali,Ashok N. Srivastava
  • Publisher : CRC Press
  • Release Date : 2012-03-29
  • Total pages : 744
  • ISBN : 0128187220
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Summary : Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines...

An Astrobiology Strategy for the Search for Life in the Universe

An Astrobiology Strategy for the Search for Life in the Universe
  • Author : National Academies of Sciences, Engineering, and Medicine,Division on Engineering and Physical Sciences,Space Studies Board,Committee on Astrobiology Science Strategy for the Search for Life in the Universe
  • Publisher : National Academies Press
  • Release Date : 2019-04-20
  • Total pages : 188
  • ISBN : 0128187220
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Summary : Astrobiology is the study of the origin, evolution, distribution, and future of life in the universe. It is an inherently interdisciplinary field that encompasses astronomy, biology, geology, heliophysics, and planetary science, including complementary laboratory activities and field studies conducted in a wide range of terrestrial environments. Combining inherent scientific interest ...