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Julia 1.0 Programming Cookbook

You're reading from Julia 1.0 Programming Cookbook

Product type Book

Published in Nov 2018

Publisher Packt

ISBN-13 9781788998369

Pages 460 pages

Edition 1st Edition

Languages

Concepts

Programming Language

Authors (2):

Bogumił Kamiński

Przemysław Szufel

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Table of Contents (18) Chapters

Title Page

Copyright and Credits

Dedication

About Packt

Contributors

Preface

1. Installing and Setting Up Julia

2. Data Structures and Algorithms

3. Data Engineering in Julia

4. Numerical Computing with Julia

5. Variables, Types, and Functions

6. Metaprogramming and Advanced Typing

7. Handling Analytical Data

8. Julia Workflow

9. Data Science

10. Distributed Computing

1. Other Books You May Enjoy

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Index

Introduction

In this chapter, we present several recipes with hints and tips on organizing workflows with Julia.

We start with Revise.jl, an essential package in any larger Julia project, which automatically reloads function definitions in packages that have changed. Next, we explain how to benchmark and profile your code. For some scenarios, Julia alone might not be enough to achieve your data science/analytical goals efficiently and hence a need arises to use other programming languages. We show how to configure and mix Julia code with code and libraries from the two most popular data science languages: Python and GNU R. Finally, we present a standard template for a Julia project.

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Authors (2)

Bogumił Kamiński

Bogumi Kamiski (GitHub username: bkamins) is an associate professor and head of the Decision Support and Analysis Unit at the SGH Warsaw School of Economics, as well as adjunct professor at the data science laboratory, Ryerson University, Toronto. He is coeditor of the Central European Journal of Economic Modeling and Econometrics, and of the Multiple Criteria Decision Making journal. His scientific interests center on operational research and computational social science. He has authored over 50 research articles on simulation, optimization, and prediction methods. He also has 15+ years' experience in the deployment of large-scale advanced analytics solutions for industry and public administration.

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Przemysław Szufel

Przemysaw Szufel (GitHub username: pszufe) is an assistant professor in the Decision Support and Analysis Unit at the SGH Warsaw School of Economics. His current research focuses on distributed systems and methods for the execution of large-scale simulations for numerical experiments and optimization. He is working on asynchronous algorithms for the parallel execution of large-scale computations in the cloud and distributed computational environments. He has authored, and co-authored, several open source tools for high-performance and numerical simulation.

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