000 04053cam a2200529Ii 4500
001 9781351013673
003 FlBoTFG
005 20220509193046.0
006 m o d
007 cr cnu---unuuu
008 190103s2018 flu ob 001 0 eng d
040 _aOCoLC-P
_beng
_erda
_epn
_cOCoLC-P
020 _a9781351013659
_q(electronic bk.)
020 _a1351013653
_q(electronic bk.)
020 _a9781351013673
_q(electronic bk.)
020 _a135101367X
_q(electronic bk.)
020 _a9781351013666
_q(electronic bk. : PDF)
020 _a1351013661
_q(electronic bk. : PDF)
020 _a9781351013642
_q(electronic bk. : Mobipocket)
020 _a1351013645
_q(electronic bk. : Mobipocket)
020 _z9781138499980
020 _z1138499986
035 _a(OCoLC)1080638155
035 _a(OCoLC-P)1080638155
050 4 _aQA76.73.J85
_bM37 2018eb
072 7 _aCOM
_x062000
_2bisacsh
072 7 _aBUS
_x061000
_2bisacsh
072 7 _aMAT
_x029000
_2bisacsh
072 7 _aUFM
_2bicssc
082 0 4 _a005.7/3
_223
100 1 _aMcNicholas, Paul D.,
_eauthor.
245 1 0 _aData science with Julia /
_cPaul D. McNicholas, Peter A. Tait.
264 1 _aBoca Raton :
_bTaylor & Francis, CRC Press,
_c2018.
300 _a1 online resource
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
520 _a"This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist."- Professor Charles Bouveyron, INRIA Chair in Data Science, Universitae Caote d'Azur, Nice, France Julia, an open-source programming language, was created to be as easy to use as languages such as R and Python while also as fast as C and Fortran. An accessible, intuitive, and highly efficient base language with speed that exceeds R and Python, makes Julia a formidable language for data science. Using well known data science methods that will motivate the reader, Data Science with Julia will get readers up to speed on key features of the Julia language and illustrate its facilities for data science and machine learning work. Features: Covers the core components of Julia as well as packages relevant to the input, manipulation and representation of data. Discusses several important topics in data science including supervised and unsupervised learning. Reviews data visualization using the Gadfly package, which was designed to emulate the very popular ggplot2 package in R. Readers will learn how to make many common plots and how to visualize model results. Presents how to optimize Julia code for performance. Will be an ideal source for people who already know R and want to learn how to use Julia (though no previous knowledge of R or any other programming language is required). The advantages of Julia for data science cannot be understated. Besides speed and ease of use, there are already over 1,900 packages available and Julia can interface (either directly or through packages) with libraries written in R, Python, Matlab, C, C++ or Fortran. The book is for senior undergraduates, beginning graduate students, or practicing data scientists who want to learn how to use Julia for data science. "This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist." Professor Charles Bouveyron INRIA Chair in Data Science Universitae Caote d'Azur, Nice, France
588 _aOCLC-licensed vendor bibliographic record.
650 0 _aJulia (Computer program language)
650 0 _aData structures (Computer science)
650 7 _aCOMPUTERS / Data Modeling & Design.
_2bisacsh
650 7 _aBUSINESS & ECONOMICS / Statistics
_2bisacsh
650 7 _aMATHEMATICS / Probability & Statistics / General
_2bisacsh
700 1 _aTait, Peter A.,
_eauthor.
856 4 0 _3Taylor & Francis
_uhttps://www.taylorfrancis.com/books/9781351013673
856 4 2 _3OCLC metadata license agreement
_uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
999 _c129068
_d129068