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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https://doi.org/10.1007/978-1-4842-3171-5Julia; programming; data science; machine learning; finance; financial; math; engineering; science; code; sour

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ICM-90 Satellite Conference Proceedingsd constructs requires time, patience, and dedicated efforts, so there should be really strong reasons to invest in such a time-consuming activity. Julia is a programming language that provides such reasons. Since there are so many established programming languages, including Python, C, C++, Java, R,

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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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https://doi.org/10.1007/978-3-658-27688-1asic knowledge of high-school-level mathematics is required for understanding the contents of this chapter. The chapter will include illustrations that represent mathematical numbers of various kinds and their algebraic operations as well as other operations used to define mathematical computations.

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A. Volyar,M. Bretsko,Ya. Akimova,Yu. Egorovactly 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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