000 03153cam a2200445 i 4500
001 1140886922
003 OCoLC
005 20250902205752.0
006 m o d
007 cr cnu|||unuuu
008 200217s2019 enk o 001 0 eng d
020 _a9781108727709
_q(electronic bk.)
020 _a9781108727709
_q(electronic bk.)
020 _z9781108727709
_q(hardback)
020 _z9781108727709
_q(paperback)
022 _a9781108727709
035 _a(OCoLC)1140886922
040 _aCAMBR
_beng
_erda
_epn
_cCAMBR
_dOCLCO
_dOCLCF
_dOCLCQ
_dK6U
050 4 _aTA340
_b.P84 2019
082 0 4 _a519.2 BEN 2019
_223
100 1 _aPrugel-Bennett, Adam,
_d1963-
_0http://id.loc.gov/authorities/names/n2019019090
_eauthor
245 1 4 _aThe probability companion for engineering and computer science /
_cAdam Prugel-Bennett
264 1 _aCambridge :
_bCambridge University Press,
_c2019
300 _a1 online resource (xv, 457 pages)
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
340 _gpolychrome
_2rdacc
_0http://rdaregistry.info/termList/RDAColourContent/1003
506 _aAvailable to OhioLINK libraries
520 _aThis friendly guide is the companion you need to convert pure mathematics into understanding and facility with a host of probabilistic tools. The book provides a high-level view of probability and its most powerful applications. It begins with the basic rules of probability and quickly progresses to some of the most sophisticated modern techniques in use, including Kalman filters, Monte Carlo techniques, machine learning methods, Bayesian inference and stochastic processes. It draws on thirty years of experience in applying probabilistic methods to problems in computational science and engineering, and numerous practical examples illustrate where these techniques are used in the real world. Topics of discussion range from carbon dating to Wasserstein GANs, one of the most recent developments in Deep Learning. The underlying mathematics is presented in full, but clarity takes priority over complete rigour, making this text a starting reference source for researchers and a readable overview for students
650 0 _aEngineering
_xStatistical methods.
_0http://id.loc.gov/authorities/subjects/sh85043194
650 0 _aComputer science
_0http://id.loc.gov/authorities/subjects/sh89003285
_xStatistical methods.
_0http://id.loc.gov/authorities/subjects/sh2001008679
650 0 _aProbabilities.
_0http://id.loc.gov/authorities/subjects/sh85107090
655 4 _aElectronic books
710 2 _aOhio Library and Information Network.
_0http://id.loc.gov/authorities/names/no95058981
856 4 0 _3OhioLINK
_zConnect to resource
_uhttps://rave.ohiolink.edu/ebooks/ebc2/9781108480536
856 4 0 _3Cambridge University Press
_zConnect to resource
_uhttps://www.cambridge.org/core/product/identifier/9781108635349/type/BOOK
856 4 0 _3Cambridge University Press
_zConnect to resource (off-campus)
_uhttps://go.ohiolink.edu/goto?url=https://www.cambridge.org/core/product/identifier/9781108635349/type/BOOK
942 _2ddc
_cBK
_n0
999 _c610
_d610