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Practical Julia

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Learn to use Julia as a research tool and tackle genuine problems, such as modeling a pandemic, in this hands-on introduction. The Julia programming language is celebrated for its ease, interactivity, and speed, making it accessible even for programming newcomers. This comprehensive guide covers Julia’s syntax, data types, and best practices, allowing you to craft solutions for challenges in fields like physics, statistics, biology, mathematics, and scientific machine learning. As you progress, you’ll explore comprehensions, generators, higher-level functions, and array manipulation, while also performing operations on Unicode text. You'll learn to create new syntax, generate code with metaprogramming and macros, and control error handling to influence program execution. Visualization techniques will help you represent mathematical constructs, experimental designs, and algorithm flowcharts effectively. Enhance performance using Julia’s unique type system and multiple dispatch, and dive into scientific packages tailored for fluid dynamics, agent-based modeling, and image processing. Whether your focus is scientific research, statistics, or simply enjoying programming, this guide will enable you to write high-performance code that accomplishes real tasks quickly. Online resources, including ready-to-run code samples and supplemental animations, are also available.

Zakup książki

Practical Julia, Lee Phillips

Język
Rok wydania
2023
Oprawa
(miękka)
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Tytuł
Practical Julia
Język
angielski
Rok wydania
2023
Oprawa
miękka
ISBN10
1718502761
ISBN13
9781718502765
Seria
Tagi
Ocena
4 z 5
Opis
Learn to use Julia as a research tool and tackle genuine problems, such as modeling a pandemic, in this hands-on introduction. The Julia programming language is celebrated for its ease, interactivity, and speed, making it accessible even for programming newcomers. This comprehensive guide covers Julia’s syntax, data types, and best practices, allowing you to craft solutions for challenges in fields like physics, statistics, biology, mathematics, and scientific machine learning. As you progress, you’ll explore comprehensions, generators, higher-level functions, and array manipulation, while also performing operations on Unicode text. You'll learn to create new syntax, generate code with metaprogramming and macros, and control error handling to influence program execution. Visualization techniques will help you represent mathematical constructs, experimental designs, and algorithm flowcharts effectively. Enhance performance using Julia’s unique type system and multiple dispatch, and dive into scientific packages tailored for fluid dynamics, agent-based modeling, and image processing. Whether your focus is scientific research, statistics, or simply enjoying programming, this guide will enable you to write high-performance code that accomplishes real tasks quickly. Online resources, including ready-to-run code samples and supplemental animations, are also available.