SKOLKOVO School of Management

Data-driven science and engineering : (Record no. 4388)

000 -LEADER
fixed length control field 01928cam a22003138i 4500
001 - CONTROL NUMBER
control field 20552686
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200213101512.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 180622s2019 enk b 001 0 eng
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 2018029888
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781108422093 (hardback : alk. paper)
040 ## - CATALOGING SOURCE
Original cataloging agency DLC
Language of cataloging eng
Description conventions rda
Transcribing agency DLC
042 ## - AUTHENTICATION CODE
Authentication code pcc
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA330
Item number .B78 2019
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 620.00285/631
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Brunton, Steven L.
Fuller form of name (Steven Lee),
Dates associated with a name 1984-
Relator term author.
245 10 - TITLE STATEMENT
Title Data-driven science and engineering :
Remainder of title machine learning, dynamical systems, and control /
Statement of responsibility, etc Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington.
263 ## - PROJECTED PUBLICATION DATE
Projected publication date 1809
300 ## - PHYSICAL DESCRIPTION
Extent pages cm
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
520 ## - SUMMARY, ETC.
Summary, etc "Data-driven discovery is revolutionizing the modelling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modelling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Aimed at advanced undergraduate and beginning graduate students in the engineering and physical sciences, the text presents a range of topics and methods from introductory to state of the art"--
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Engineering
General subdivision Data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Science
General subdivision Data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mathematical analysis.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Kutz, Jose Nathan,
Relator term author.
856 ## - ELECTRONIC LOCATION AND ACCESS
Materials specified Full-text here
Uniform Resource Identifier https://www.cambridge.org/core/books/datadriven-science-and-engineering/77D52B171B60A496EAFE4DB662ADC36E
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN)
a 7
b cbc
c orignew
d 1
e ecip
f 20
g y-gencatlg
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type Book
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Permanent Location Current Location Shelving location Date acquired Total Checkouts Total Renewals Full call number Barcode Date last seen Date checked out Price effective from Koha item type
          Skoltech library Skoltech library Shelves 2019-10-21 1 1 TA330 .B78 2019 2000007738 2022-01-25 2021-09-03 2019-10-21 Book