
Data-Driven Modeling & Scientific Computation
methods for complex systems & big data
$198.48
- Paperback
656 pages
- Release Date
18 September 2013
Summary
Unveiling Insights: Data-Driven Modeling and Scientific Computation
The explosive growth of data analysis, fueled by widespread data collection across scientific disciplines, necessitates innovative mathematical techniques and computational algorithms. These tools are crucial for synthesizing, interpreting, and extracting meaningful insights from complex datasets within their scientific context.
This book bridges the gap between standard scientific computing methods and data…
Book Details
ISBN-13: | 9780199660346 |
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ISBN-10: | 0199660344 |
Author: | J. Nathan Kutz |
Publisher: | Oxford University Press |
Imprint: | Oxford University Press |
Format: | Paperback |
Number of Pages: | 656 |
Release Date: | 18 September 2013 |
Weight: | 1.36kg |
Dimensions: | 245mm x 191mm x 31mm |
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What They're Saying
Critics Review
The book allows methods for dealing with large data to be explained in a logical process suitable for both undergraduate and post-graduate students … With sport performance analysis evolving into deal with big data, the book forms a key bridge between mathematics and sport science * John Francis, University of Worcester *
About The Author
J. Nathan Kutz
Professor Kutz is the Robert Bolles and Yasuko Endo Professor of Applied Mathematics at the University of Washington. Prof. Kutz was awarded the B.S. in physics and mathematics from the University of Washington (Seattle, WA) in 1990 and the PhD in Applied Mathematics from Northwestern University (Evanston, IL) in 1994. He joined the Department of Applied Mathematics, University of Washington in 1998 and became Chair in 2007.
Professor Kutz is especially interested in a unified approach to applied mathematics that includes modeling, computation and analysis. His area of current interest concerns phenomena in complex systems and data analysis (dimensionality reduction, compressive sensing, machine learning), neuroscience (neuro-sensory systems, networks of neurons), and the optical sciences (laser dynamics and modelocking, solitons, pattern formation in nonlinear optics).
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