001451884 000__ 03307cam\a2200493\a\4500
001451884 001__ 1451884
001451884 003__ OCoLC
001451884 005__ 20230310004722.0
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001451884 007__ cr\un\nnnunnun
001451884 008__ 221217s2022\\\\sz\\\\\\ob\\\\001\0\eng\d
001451884 019__ $$a1354993628$$a1355372473
001451884 020__ $$a9783031165603$$q(electronic bk.)
001451884 020__ $$a3031165608$$q(electronic bk.)
001451884 020__ $$z3031165594
001451884 020__ $$z9783031165597
001451884 0247_ $$a10.1007/978-3-031-16560-3$$2doi
001451884 035__ $$aSP(OCoLC)1355216733
001451884 040__ $$aEBLCP$$beng$$cEBLCP$$dGW5XE$$dYDX$$dFIE$$dOCLCF$$dUKAHL
001451884 049__ $$aISEA
001451884 050_4 $$aQA76.9.A43
001451884 08204 $$a005.13$$223/eng/20230109
001451884 1001_ $$aHeitzinger, Clemens.
001451884 24510 $$aAlgorithms with JULIA :$$boptimization, machine learning, and differential Equations using the JULIA language /$$cClemens Heitzinger.
001451884 260__ $$aCham :$$bSpringer,$$c2022.
001451884 300__ $$a1 online resource (447 p.)
001451884 336__ $$atext$$btxt$$2rdacontent
001451884 337__ $$acomputer$$bc$$2rdamedia
001451884 338__ $$aonline resource$$bcr$$2rdacarrier
001451884 504__ $$aIncludes bibliographical references and index.
001451884 5050_ $$aAn Introduction to the Julia Language -- Functions -- Variables, Constants, Scopes, and Modules -- Built-in Data Structures -- User Defined Data Structures and the Type System -- Control Flow -- Macros -- Arrays and Linear Algebra -- Ordinary Differential Equations -- Partial-Differential Equations -- Global Optimization -- Local Optimization -- Neural Networks -- Bayesian Estimation.
001451884 506__ $$aAccess limited to authorized users.
001451884 520__ $$aThis book provides an introduction to modern topics in scientific computing and machine learning, using JULIA to illustrate the efficient implementation of algorithms. In addition to covering fundamental topics, such as optimization and solving systems of equations, it adds to the usual canon of computational science by including more advanced topics of practical importance. In particular, there is a focus on partial differential equations and systems thereof, which form the basis of many engineering applications. Several chapters also include material on machine learning (artificial neural networks and Bayesian estimation). JULIA is a relatively new programming language which has been developed with scientific and technical computing in mind. Its syntax is similar to other languages in this area, but it has been designed to embrace modern programming concepts. It is open source, and it comes with a compiler and an easy-to-use package system. Aimed at students of applied mathematics, computer science, engineering and bioinformatics, the book assumes only a basic knowledge of linear algebra and programming.
001451884 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed January 9, 2023).
001451884 650_0 $$aComputer algorithms.
001451884 650_0 $$aJulia (Computer program language)
001451884 655_0 $$aElectronic books.
001451884 77608 $$iPrint version:$$aHeitzinger, Clemens$$tAlgorithms with JULIA$$dCham : Springer International Publishing AG,c2023$$z9783031165597
001451884 852__ $$bebk
001451884 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-16560-3$$zOnline Access$$91397441.1
001451884 909CO $$ooai:library.usi.edu:1451884$$pGLOBAL_SET
001451884 980__ $$aBIB
001451884 980__ $$aEBOOK
001451884 982__ $$aEbook
001451884 983__ $$aOnline
001451884 994__ $$a92$$bISE