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Learning Julia. Build high-performance applications for scientific computing Anshul Joshi, Rahul Lakhanpal

(ebook) (audiobook) (audiobook) Książka w języku 1
Learning Julia. Build high-performance applications for scientific computing Anshul Joshi, Rahul Lakhanpal - okladka książki

Learning Julia. Build high-performance applications for scientific computing Anshul Joshi, Rahul Lakhanpal - okladka książki

Learning Julia. Build high-performance applications for scientific computing Anshul Joshi, Rahul Lakhanpal - audiobook MP3

Learning Julia. Build high-performance applications for scientific computing Anshul Joshi, Rahul Lakhanpal - audiobook CD

Autorzy:
Anshul Joshi, Rahul Lakhanpal
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
316
Dostępne formaty:
     PDF
     ePub
     Mobi
Julia is a highly appropriate language for scientific computing, but it comes with all the required capabilities of a general-purpose language. It allows us to achieve C/Fortran-like performance while maintaining the concise syntax of a scripting language such as Python. It is perfect for building high-performance and concurrent applications. From the basics of its syntax to learning built-in object types, this book covers it all.

This book shows you how to write effective functions, reduce code redundancies, and improve code reuse. It will be helpful for new programmers who are starting out with Julia to explore its wide and ever-growing package ecosystem and also for experienced developers/statisticians/data scientists who want to add Julia to their skill-set.

The book presents the fundamentals of programming in Julia and in-depth informative examples, using a step-by-step approach. You will be taken through concepts and examples such as doing simple mathematical operations, creating loops, metaprogramming, functions, collections, multiple dispatch, and so on.

By the end of the book, you will be able to apply your skills in Julia to create and explore applications of any domain.

Wybrane bestsellery

O autorach książki

Anshul Joshi is a data scientist with experience in recommendation systems, predictive modeling, neural networks, and high performance computing. His research interests encompass deep learning, artificial intelligence, and computational physics. Most of the time, he can be caught exploring GitHub or trying anything new he can get his hands on. You can also follow his personal blog.
Rahul Lakhanpal is a technology and open source enthusiast. With diversified skills including systems engineering, web development, the cloud, and big data, he is language-agnostic and a firm believer in using the best tools and the right language for a particular job. Rahul is an active contributor to various community portals and loves to solve challenging real-world problems in his leisure time. He is active on Twitter and writes blogs as well.

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