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|a 9781484251904
|9 978-1-4842-5190-4
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|a 10.1007/978-1-4842-5190-4
|2 doi
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|d GrThAP
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|a QA76.7-76.73
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|a 005.13
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|a Lobianco, Antonello.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Julia Quick Syntax Reference
|h [electronic resource] :
|b A Pocket Guide for Data Science Programming /
|c by Antonello Lobianco.
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|a 1st ed. 2019.
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|a Berkeley, CA :
|b Apress :
|b Imprint: Apress,
|c 2019.
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|a XVII, 216 p. 66 illus.
|b online resource.
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|a text
|b txt
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|a computer
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|a online resource
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|a text file
|b PDF
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|a Part 1. Language Core -- 1. Getting Started -- 2. Data Types and Structures -- 3. Control Flow and Functions -- 4. Custom Types -- 5. Input - Output -- 6. Metaprogramming and Macros -- 7. Interfacing Julia with Other Languages -- 8. Efficiently Write Efficient Code -- Part 2. Packages Ecosystem -- 9. Working with Data -- 10. Mathematical Libraries -- 11. Utilities.
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|a This quick Julia programming language guide is a condensed code and syntax reference to the Julia 1.x programming language, updated with the latest features of the Julia APIs, libraries, and packages. It presents the essential Julia syntax in a well-organized format that can be used as a handy reference. This book provides an introduction that reveals basic Julia structures and syntax; discusses data types, control flow, functions, input/output, exceptions, metaprogramming, performance, and more. Additionally, you'll learn to interface Julia with other programming languages such as R for statistics or Python. You will learn how to use Julia packages for data analysis, numerical optimization and symbolic computation, and how to disseminate your results in dynamic documents or interactive web pages. In this book, the focus is on providing important information as quickly as possible. It is packed with useful information and is a must-have for any Julia programmer. You will: Set up the software needed to run Julia and your first Hello World example Work with types and the different containers that Julia makes available for rapid application development Use vectorized, classical loop-based code such as logical operators and blocks Explore functions by looking at arguments, return values, polymorphism, parameters, anonymous functions, and broadcasts Build custom structures in Julia Interface Julia with other languages such as C/C++, Python, and R Program a richer API, modifying the code before it is executed using expressions, symbols, macros, quote blocks, and more Maximize your code's performance .
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|a Programming languages (Electronic computers).
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|a Artificial intelligence.
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|a Data mining.
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|a Computer science-Mathematics.
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|a Programming Languages, Compilers, Interpreters.
|0 http://scigraph.springernature.com/things/product-market-codes/I14037
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|a Artificial Intelligence.
|0 http://scigraph.springernature.com/things/product-market-codes/I21000
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|a Data Mining and Knowledge Discovery.
|0 http://scigraph.springernature.com/things/product-market-codes/I18030
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|a Mathematics of Computing.
|0 http://scigraph.springernature.com/things/product-market-codes/I17001
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|a SpringerLink (Online service)
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|t Springer eBooks
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776 |
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|i Printed edition:
|z 9781484251898
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|i Printed edition:
|z 9781484251911
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|u https://doi.org/10.1007/978-1-4842-5190-4
|z Full Text via HEAL-Link
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|a ZDB-2-CWD
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|a Professional and Applied Computing (Springer-12059)
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