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Julia 1.0 Programming Cookbook
Julia 1.0 Programming Cookbook

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

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Profile Icon Kamiński Profile Icon Szufel
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S$46.99 S$52.99
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.3 (4 Ratings)
eBook Nov 2018 460 pages 1st Edition
eBook
S$46.99 S$52.99
Paperback
S$66.99
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Arrow left icon
Profile Icon Kamiński Profile Icon Szufel
Arrow right icon
S$46.99 S$52.99
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.3 (4 Ratings)
eBook Nov 2018 460 pages 1st Edition
eBook
S$46.99 S$52.99
Paperback
S$66.99
Subscription
Free Trial
eBook
S$46.99 S$52.99
Paperback
S$66.99
Subscription
Free Trial

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Julia 1.0 Programming Cookbook

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Key benefits

  • 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

Description

Julia, 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

Who is this book 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.

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

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Nov 29, 2018
Length: 460 pages
Edition : 1st
Language : English
ISBN-13 : 9781788998826
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Product Details

Publication date : Nov 29, 2018
Length: 460 pages
Edition : 1st
Language : English
ISBN-13 : 9781788998826
Category :
Languages :

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Table of Contents

11 Chapters
Installing and Setting Up Julia Chevron down icon Chevron up icon
Data Structures and Algorithms Chevron down icon Chevron up icon
Data Engineering in Julia Chevron down icon Chevron up icon
Numerical Computing with Julia Chevron down icon Chevron up icon
Variables, Types, and Functions Chevron down icon Chevron up icon
Metaprogramming and Advanced Typing Chevron down icon Chevron up icon
Handling Analytical Data Chevron down icon Chevron up icon
Julia Workflow Chevron down icon Chevron up icon
Data Science Chevron down icon Chevron up icon
Distributed Computing Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.3
(4 Ratings)
5 star 50%
4 star 0%
3 star 0%
2 star 25%
1 star 25%
General Malfunction Jan 12, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I have been developing large scale simulation models for many years now, mostly in Java. Recently I decided to check out Julia in this area. This book caught my attention, because it featured recipes directly from my field of interest such as Monte Carlo simulation or modeling queuing systems. The biggest benefit from reading it was understanding how to implement numerical computing routines efficiently in Julia (which is a pain in Java). Also the last chapter on distributed computing was very valuable, as I have found that with the functionalities shipped with the language I am was scale my simulations very easily. I think that the book is relatively well written, however, I would say that beginners might find it challenging, as it assumes that the reader has some basic knowledge of Julia and computing principles in general.
Amazon Verified review Amazon
Pawel Pralat Jan 12, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I am a research scientist (professor of mathematics) with past experience in using C/C++ (for heavy number crunching) and Maple (for everything else).After studying the recipes in the book, I now see that Julia is a great language that combines easy code (such as Maple or Python) and speed of C. For other researchers I would especially recommend Chapter 4: “Numerical Computing with Julia”, where one can learn how to write high-performance Julia code. Also Chapter 1: “Installing and Setting Up Julia” saved me a lot of time, as usually starting using a new computational environment requires to learn a lot of small details, which are nicely laid out in the book. Julia is famous for its ease to scale out the computations for many CPU cores and nodes. The recipes in the Chapter 10, "Distributed Computing", turned to be great companion to the existing Julia documentation. To book presents Julia high performance computing from a very practical perspective and made it much easier to scale out scientific computations.
Amazon Verified review Amazon
DrJimbo Dec 17, 2018
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
I was somewhat optimistic that this publication would be worthwhile insofar as one of the authors is a very frequent and helpful contributor to Julia support on StackOverflow. Regrettably this was not to be.For example, Chapter 1 provides a fairly thorough overview of Julia program installation along with various IDE's for Windows and Linux Ubuntu - iOS/mac systems are not even referenced! Now this is probably due to the authors residing in Poland where iOS/mac systems are less prevalent, but this publication is being promoted in the U.S. where iOS/mac systems are very prevalent especially in technical computing environments.Let's consider Chapter 2 - Data Structures and AlgorithmsConsider the first example - Finding the index of a random minimum element in an array. The authors launch right into the creation of functions which employ arrays without bothering to discuss the nature of function definitions or arrays. Moreover the second function in the section is relatively complex and involves Julia programming structures previously unmentioned, let alone discussed in detail until much later in the book. Later in Chapter #2 there is a far more complex set of functions to optimize matrix multiplication, perhaps valuable in numerical programming contexts but not necessarily a cookbook example of substantial urgency, especially so early in the volume.Chapter 5 - Variables, Types and Function. Put to the side for the moment that Chapters 2 through 4 have been making extensive use of these three aspects of Julia programming so this chapter arrives a bit late in the game. To begin the discussion of types Julia structures are used - would you like see where structures are thoroughly reviewed? Forget about looking at the Index in the back of the book - "Sudoku" is there, but no "struct". In short, you are left to understand the nature of structures while in the midst of a section on types and type hierarchy.While not altogether unworthy this volume betrays an all too frequent issue with Packt publications - no responsible editorial review. By way of comparison, O'Reilly technical publications, but particularly their "Cookbooks", are wonderfully organized and employ examples which are widely relevant and progress methodically from the simple to the more complex.Given the freely available Julia programing resources this volume is to my mind of tertiary value.
Amazon Verified review Amazon
Marcello Vitaletti Dec 24, 2019
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
Many math expressions are unreadable in the Kindle edition
Amazon Verified review Amazon
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