LargeScale Machine Learning in the Earth Sciences (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series),Used

LargeScale Machine Learning in the Earth Sciences (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series),Used

In Stock
SKU: DADAX1498703879
UPC: 1498703879
Brand: CRC Press
$171.68 $245.26
Save $73.58
Quantity
Add to wishlist
Add to compare

Processing time: 1-3 days

US Orders Ships in: 3-5 days

International Orders Ships in: 8-12 days

Return Policy: 15-days return on defective items

Payment Option
Payment Methods

Help

If you have any questions, you are always welcome to contact us. We'll get back to you as soon as possible, withing 24 hours on weekdays.

Customer service

All questions about your order, return and delivery must be sent to our customer service team by e-mail at yourstore@yourdomain.com

Sale & Press

If you are interested in selling our products, need more information about our brand or wish to make a collaboration, please contact us at press@yourdomain.com

From the Foreword:"While largescale 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 interestI 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 MinnesotaLargeScale 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 stateoftheart 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 largescale 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 longtail distributions to geoscience resources, in the final chapter of the book.

⚠️ WARNING (California Proposition 65):

This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.

For more information, please visit www.P65Warnings.ca.gov.

Recently Viewed