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Learning Julia

You're reading from Learning Julia Build high-performance applications for scientific computing

Product type Paperback

Published in Nov 2017

Publisher Packt

ISBN-13 9781785883279

Length 316 pages

Edition 1st Edition

Languages

Julia

Concepts

Programming Language

Authors (2):

Rahul Lakhanpal

Anshul Joshi

View More author details

Table of Contents (11) Chapters

Preface

1. Understanding Julia's Ecosystem FREE CHAPTER

2. Programming Concepts with Julia

3. Functions in Julia

4. Understanding Types and Dispatch

5. Working with Control Flow

6. Interoperability and Metaprogramming

7. Numerical and Scientific Computation with Julia

8. Data Visualization and Graphics

9. Connecting with Databases

10. Julia’s Internals

Summary

In this chapter, we learned how we can run C as well as Python codes in Julia. We also went on to study how one interacts with the operating system internals, including the filesystem and I/O-related tasks. We then moved forward to learn and explore the world of metaprogramming, where we read in detail about what expressions are, and how one can create macros, as well as use the already provided built-in macros.

In the next chapter, we will be using all the knowledge gained so far to apply our learning of the Julia language, and we'll work together to make the most of it for mathematical as well as for statistical purposes.

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Authors (2)

Lakhanpal

Lakhanpal

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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Anshul Joshi

Anshul Joshi

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.

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