Book > Machine Learning For Planetary Science

Machine Learning for Planetary Science

Machine Learning for Planetary Science

Detail Book : Machine Learning for Planetary Science written by Joern Helbert, published by Elsevier which was released on 01 March 2021. Download Machine Learning for Planetary Science Books now! Available in PDF, ePub and Kindle. 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

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Author : Joern Helbert
Release Date : 01 March 2021
Publisher : Elsevier
Rating : 4/5 (from 21 users)
Pages : 400
ISBN : 0128187220
Format : PDF, ePUB, KF8, PDB, MOBI, Tuebl
Machine Learning for Planetary Science

Machine Learning for Planetary Science

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

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Machine Learning Techniques for Space Weather

Machine Learning Techniques for Space Weather

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,

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Machine Learning and Artificial Intelligence in Geosciences

Machine Learning and Artificial Intelligence in Geosciences

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

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Advances in Machine Learning and Data Mining for Astronomy

Advances in Machine Learning and Data Mining for Astronomy

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, the material discussed in

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Earth Observation Open Science and Innovation

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This book is published open access under a CC BY 4.0 license. Over the past decades, rapid developments in digital and sensing technologies, such as the Cloud, Web and Internet of Things, have dramatically changed the way we live and work. The digital transformation is revolutionizing our ability to monitor our

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Machine Learning on Mars

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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

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Machine Learning Methods in the Environmental Sciences

Machine Learning Methods in the Environmental Sciences

A graduate textbook that provides a unified treatment of machine learning methods and their applications in the environmental sciences.

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Machine Learning

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One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build computers capable of improving their performance with practice and of

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Knowledge Discovery in Big Data from Astronomy and Earth Observation

Knowledge Discovery in Big Data from Astronomy and Earth Observation

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

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Using Machine Learning for Hydrocarbon Prospecting in Reconcavo Basin  Brazil

Using Machine Learning for Hydrocarbon Prospecting in Reconcavo Basin Brazil

Machine Learning techniques are being widely used in Social Sciences to find connections amongst various variables. Machine Learning connects features across different fields that do not seem to have known mathematical relationships with each other. In natural resource prospecting, machine learning can be applied to connect geochemical, geophysical, and geological

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Explainable AI  Interpreting  Explaining and Visualizing Deep Learning

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The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving

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Machine Learning and Data Mining in Pattern Recognition

Machine Learning and Data Mining in Pattern Recognition

There is no royal road to science, and only those who do not dread the fatiguing climb of its steep paths have a chance of gaining its luminous summits. Karl Marx A Universial Genius of the 19th Century Many scientists from all over the world during the past two years

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Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification

Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification

This book covers the state-of-art image classification methods for discrimination of earth objects from remote sensing satellite data with an emphasis on fuzzy machine learning and deep learning algorithms. Both types of algorithms are described in such details that these can be implemented directly for thematic mapping of multiple-class or

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Space Science and Astronomy Theatre

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If youre a teacher or parent struggling to get youngsters or young adults interested in space science and astronomyor an inquisitive studentthen youll love this fun-filled book of theatrical scenes. In addition to astronomers and astronauts, the scenes also feature engineers, accountants, graphic artists, public relations practitioners, biologists, meteorologists, and

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HUD space science veterans Appropriations for 1975

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