Data-Driven Modeling & Scientific Computation: Methods for Complex Systems & Big Data
Autor J. Nathan Kutzen Limba Engleză Paperback – 21 mai 2026
| Toate formatele și edițiile | Preț | Express |
|---|---|---|
| Paperback (2) | 381.01 lei 23-29 zile | +105.67 lei 7-11 zile |
| Oxford University Press – 8 aug 2013 | 381.01 lei 23-29 zile | +105.67 lei 7-11 zile |
| OUP OXFORD – 21 mai 2026 | 342.45 lei Precomandă | |
| Hardback (2) | 770.06 lei 44-50 zile | |
| OUP OXFORD – 8 aug 2013 | 770.06 lei 44-50 zile | |
| OUP OXFORD – 21 mai 2026 | 879.69 lei Precomandă |
Preț: 342.45 lei
Preț vechi: 384.29 lei
-11% Precomandă
Puncte Express: 514
Preț estimativ în valută:
60.60€ • 71.15$ • 53.19£
60.60€ • 71.15$ • 53.19£
Carte nepublicată încă
Doresc să fiu notificat când acest titlu va fi disponibil:
Se trimite...
Preluare comenzi: 021 569.72.76
Specificații
ISBN-13: 9780198929086
ISBN-10: 0198929080
Pagini: 576
Ilustrații: 240 b/w illustrations
Dimensiuni: 189 x 246 mm
Editura: OUP OXFORD
Colecția OUP Oxford
Locul publicării:Oxford, United Kingdom
ISBN-10: 0198929080
Pagini: 576
Ilustrații: 240 b/w illustrations
Dimensiuni: 189 x 246 mm
Editura: OUP OXFORD
Colecția OUP Oxford
Locul publicării:Oxford, United Kingdom
Recenzii
Review from previous edition 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
Notă biografică
J. Nathan Kutz is the Boeing Professor of AI and Data-Driven Modeling at the University of Washington. He is with the Department of Applied Mathematics and Electrical and Computer Engineering and is also Director of the AI Institute in Dynamic Systems at the University of Washington. He received the BS degree in physics and mathematics from the University of Washington in 1990 and the PhD in applied mathematics from Northwestern University in 1994. He was a postdoc in the applied and computational mathematics program at Princeton University before taking his faculty position. He has a wide range of interests, including neuroscience to fluid dynamics where he integrates machine learning with dynamical systems and control.