Large-Scale Machine Learning in the Earth Sciences / (Record no. 72315)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 05946cam a2200541Mi 4500 |
| 001 - CONTROL NUMBER | |
| control field | 9781498703888 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220711212841.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 170717s2016 flua o 000 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781315371740 |
| -- | (e-book ; |
| -- | PDF) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 131537174X |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781498703888 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 1498703887 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781315335407 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 1315335409 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781498703871 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 1498703879 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 550.2856312 |
| 100 1# - AUTHOR NAME | |
| Author | Srivastava, Ashok N., |
| 245 10 - TITLE STATEMENT | |
| Title | Large-Scale Machine Learning in the Earth Sciences / |
| 250 ## - EDITION STATEMENT | |
| Edition statement | First edition. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | 1 online resource : |
| 490 1# - SERIES STATEMENT | |
| Series statement | Chapman & Hall/CRC Data Mining and Knowledge Discovery Series |
| 520 2# - SUMMARY, ETC. | |
| Summary, etc | "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 AshokSrivastava, Ramakrishna Nemani, and Karsten Steinhaeuser, serves as an outstanding resource for anyone interested in the opportunities and challenges for the machine learning community in analyzing these data sets to answer questions of urgent societal interest ... I hope that this book will inspire more computer scientists to focus on environmental applications, and Earth scientists to seek collaborations with researchers in machine learning and data mining to advance the frontiers in Earth sciences."--Vipin Kumar, University of MinnesotaLarge-Scale Machine Learning in the Earth Sciences provides researchers and practitioners with a broad overview of some of the key challenges in the intersection of Earth science, computer science, statistics, and related fields. It explores a wide range of topics and provides a compilation of recent research in the application of machine learning in the field of Earth Science. Making predictions based on observational data is a theme of the book, and the book includes chapters on the use of network science to understand and discover teleconnections in extreme climate and weather events, as well as using structured estimation in high dimensions. The use of ensemble machine learning models to combine predictions of global climate models using information from spatial and temporal patterns is also explored. The second part of the book features a discussion on statistical downscaling in climate with state-of-the-art scalable machine learning, as well as an overview of methods to understand and predict the proliferation of biological species due to changes in environmental conditions. The problem of using large-scale machine learning to study the formation of tornadoes is also explored in depth. The last part of the book covers the use of deep learning algorithms to classify images that have very high resolution, as well as the unmixing of spectral signals in remote sensing images of land cover. The authors also apply long-tail distributions to geoscience resources, in the final chapter of the book."--Provided by publisher. |
| 650 07 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| General subdivision | Machine Theory. |
| 650 07 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| General subdivision | Earth Sciences |
| -- | General. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| General subdivision | Computer network resources. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| General subdivision | Data processing. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Nemani, Ramakrishna. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Steinhaeuser, Karsten. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://www.taylorfrancis.com/books/9781498703888 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://www.taylorfrancis.com/books/9781315371740 |
| 856 42 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Boca Raton, FL : |
| -- | CRC Press, |
| -- | 2016. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 588 ## - | |
| -- | OCLC-licensed vendor bibliographic record. |
| 650 07 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | COMPUTERS |
| 650 07 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | SCIENCE |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Earth sciences |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Earth sciences |
| 938 ## - | |
| -- | Taylor & Francis |
| -- | TAFR |
| -- | 9781315371740 |
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