Julia 1.0 Programming Cookbook: Over 100 numerical and distributed computing recipes for your daily data science work?ow

Name: Julia 1.0 Programming Cookbook: Over 100 numerical and distributed computing recipes for your daily data science work?ow
Rating: 3 (1 reviews)

Bogumił Kamiński · Przemysław Szufel

Nov 2018 · Packt Publishing Ltd

1 review

Ebook

460

Pages

Tools

About this ebook

Discover the new features and widely used packages in Julia to solve complex computational problems in your statistical applications. Key Features

Address the core problems of programming in Julia with the most popular packages for common tasks
Tackle issues while working with Databases and Parallel data processing with Julia
Explore advanced features such as metaprogramming, functional programming, and user defined types

Book DescriptionJulia, with its dynamic nature and high-performance, provides comparatively minimal time for the development of computational models with easy-to-maintain computational code. This book will be your solution-based guide as it will take you through different programming aspects with Julia. Starting with the new features of Julia 1.0, each recipe addresses a specific problem, providing a solution and explaining how it works. You will work with the powerful Julia tools and data structures along with the most popular Julia packages. You will learn to create vectors, handle variables, and work with functions. You will be introduced to various recipes for numerical computing, distributed computing, and achieving high performance. You will see how to optimize data science programs with parallel computing and memory allocation. We will look into more advanced concepts such as metaprogramming and functional programming. Finally, you will learn how to tackle issues while working with databases and data processing, and will learn about on data science problems, data modeling, data analysis, data manipulation, parallel processing, and cloud computing with Julia. By the end of the book, you will have acquired the skills to work more effectively with your data What you will learn

Boost your code's performance using Julia's unique features
Organize data in to fundamental types of collections: arrays and dictionaries
Organize data science processes within Julia and solve related problems
Scale Julia computations with cloud computing
Write data to IO streams with Julia and handle web transfer
Define your own immutable and mutable types
Speed up the development process using metaprogramming

Who this book is for

The target audience of this book is data scientists or programmers that want to improve their skills in working with the Julia programming language. It is recommended that the user has a little experience with Julia or intermediate-level experience with other programming languages such as Python, R, or MATLAB.

Discover the new features and widely used packages in Julia to solve complex computational problems in your statistical applications. Key Features Address the core problems of programming in Julia with the most popular packages for common tasks Tackle issues while working with Databases and Paral...

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Ratings and reviews

1 review

About the author

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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