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Titlebook: Beginning Julia Programming; For Engineers and Sc Sandeep Nagar Book 2017 Sandeep Nagar 2017 Julia.programming.data science.machine learnin

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發(fā)表于 2025-3-21 20:00:39 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱(chēng)Beginning Julia Programming
期刊簡(jiǎn)稱(chēng)For Engineers and Sc
影響因子2023Sandeep Nagar
視頻videohttp://file.papertrans.cn/183/182408/182408.mp4
發(fā)行地址Obtain core skills in Julia.Learn to apply Julia in engineering and science applications.Master the use of arrays, strings, functions, control flow, and I/O in Julia
圖書(shū)封面Titlebook: Beginning Julia Programming; For Engineers and Sc Sandeep Nagar Book 2017 Sandeep Nagar 2017 Julia.programming.data science.machine learnin
影響因子Get started with Julia for engineering and numerical computing, especially data science, machine learning, and scientific computing applications. This book explains how Julia provides the functionality, ease-of-use and intuitive syntax of R, Python, MATLAB, SAS, or Stata combined with the speed, capacity, and performance of C, C++, or Java. You’ll learn the OOP principles required to get you started, then how to do basic mathematics with Julia. Other core functionality of Julia that you’ll cover, includes working with complex numbers, rational and irrational numbers, rings, and fields. ?.Beginning Julia Programming. takes you beyond these basics to harness Julia’s powerful features for mathematical functions in Julia, arrays for matrix operations, plotting, and more. Along the way, you also learn how to manage strings, write functions, work with control flows, and carry out I/O to implement and leverage the mathematics needed for your data scienceand analysis projects.."Julia walks like Python and runs like C". This phrase explains why Julia is quickly growing as the most favored option for data analytics and numerical computation. After reading and using this book, you‘ll have the
Pindex Book 2017
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發(fā)表于 2025-3-21 20:36:25 | 只看該作者
Object-Oriented Programming,ting community. The ease of defining a computational problem in OOP made it a famous computing paradigm; hence, Julia also adopted OOP. To learn Julia, getting to know OOP is a prerequisite. We have dedicated this chapter for this purpose.
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Mathematical Functions,actly one output. Most users are already familiar with many such functions including the trigonometric functions sin(x), cos(x), and tan(x); logarithms to the base of a number—say 10—as log10(x); exponentiation ex; and so on. A programming language boasting to perform complex mathematical calculatio
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Plotting,non. Also, in today’s world, publications are becoming benchmarks of academic success, and good publications require attractive graphs and animations for showcasing results. For these reasons, plotting 2D and 3D graphs as well as making animations for a given process/equation is an essential part of
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Metaprogramming,ing other parts of source files to an extent that it can modify them and control their execution. To understand this process, you must understand the way Julia code is executed. Broadly speaking, there are two stages of Julia code execution
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https://doi.org/10.1007/978-3-658-27688-1ting community. The ease of defining a computational problem in OOP made it a famous computing paradigm; hence, Julia also adopted OOP. To learn Julia, getting to know OOP is a prerequisite. We have dedicated this chapter for this purpose.
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發(fā)表于 2025-3-23 07:58:28 | 只看該作者
A. Volyar,M. Bretsko,Ya. Akimova,Yu. Egorovving complex numbers can be found in almost all branches of science and mathematics. All Julia-based numerical computation developers must understand a variety of ways of defining complex numbers and their mathematics to compute efficiently.
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