000 | 04053cam a2200529Ii 4500 | ||
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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 |
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020 |
_a9781351013659 _q(electronic bk.) |
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020 |
_a1351013653 _q(electronic bk.) |
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020 |
_a9781351013673 _q(electronic bk.) |
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020 |
_a135101367X _q(electronic bk.) |
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020 |
_a9781351013666 _q(electronic bk. : PDF) |
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020 |
_a1351013661 _q(electronic bk. : PDF) |
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020 |
_a9781351013642 _q(electronic bk. : Mobipocket) |
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020 |
_a1351013645 _q(electronic bk. : Mobipocket) |
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020 | _z9781138499980 | ||
020 | _z1138499986 | ||
035 | _a(OCoLC)1080638155 | ||
035 | _a(OCoLC-P)1080638155 | ||
050 | 4 |
_aQA76.73.J85 _bM37 2018eb |
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072 | 7 |
_aCOM _x062000 _2bisacsh |
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_aBUS _x061000 _2bisacsh |
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_aMAT _x029000 _2bisacsh |
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072 | 7 |
_aUFM _2bicssc |
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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. |
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300 | _a1 online resource | ||
336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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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 |
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650 | 7 |
_aBUSINESS & ECONOMICS / Statistics _2bisacsh |
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650 | 7 |
_aMATHEMATICS / Probability & Statistics / General _2bisacsh |
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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 |