Julia Cookbook

Jalem Raj Rohit

• Publisher: Packt Publishing
• Year: 2016
• ISBN:
  9781785882012
• Edition: 1
• Topic: Computer Science
• Subtopic: Parallel Programming
• Index: Computer Science

Over 40 recipes to get you up and running with programming using Julia

About This Book

• Follow a practical approach to learn Julia programming the easy way
• Get an extensive coverage of Julia's packages for statistical analysis
• This recipe-based approach will help you get familiar with the key concepts in Juli

Who This Book Is For

This book is for data scientists and data analysts who are familiar with the basics of the Julia language. Prior experience of working with high-level languages such as MATLAB, Python, R, or Ruby is expected.

What You Will Learn

• Extract and handle your data with Julia
• Uncover the concepts of metaprogramming in Julia
• Conduct statistical analysis with StatsBase.jl and Distributions.jl
• Build your data science models
• Find out how to visualize your data with Gadfly
• Explore big data concepts in Julia

In Detail

Want to handle everything that Julia can throw at you and get the most of it every day? This practical guide to programming with Julia for performing numerical computation will make you more productive and able work with data more efficiently. The book starts with the main features of Julia to help you quickly refresh your knowledge of functions, modules, and arrays. We'll also show you how to utilize the Julia language to identify, retrieve, and transform data sets so you can perform data analysis and data manipulation.

Later on, you'll see how to optimize data science programs with parallel computing and memory allocation. You'll get familiar with the concepts of package development and networking to solve numerical problems using the Julia platform.

This book includes recipes on identifying and classifying data science problems, data modelling, data analysis, data manipulation, meta-programming, multidimensional arrays, and parallel computing. By the end of the book, you will acquire the skills to work more effectively with your data.

Style and approach

This book has a recipe-based approach to help you grasp the concepts of Julia programming.

Julia Cookbook

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Julia Cookbook

Copyright © 2016 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

First published: September 2016

Production reference: 1260916

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham B3 2PB, UK.

ISBN 978-1-78588-201-2

www.packtpub.com

Credits

Author Jalem Raj Rohit	Copy Editor Pranjali Chury
Reviewer Jakub Glinka	Project Coordinator Izzat Contractor
Commissioning Editor Pratik Shah	Proofreader Safis Editing
Acquisition Editor Denim Pinto	Indexer Tejal Daruwale Soni
Content Development Editor Rohit Singh	Production Coordinator Aparna Bhagat
Technical Editor Abhishek R. Kotian	Cover Work Aparna Bhagat

About the Author

Jalem Raj Rohit is an IIT Jodhpur graduate with a keen interest in machine learning, data science, data analysis, computational statistics, and natural language processing (NLP). Rohit currently works as a senior data scientist at Zomato, also having worked as the first data scientist at Kayako.

He is part of the Julia project, where he develops data science models and contributes to the codebase. Additionally, Raj is also a Mozilla contributor and volunteer, and he has interned at Scimergent Analytics.

I would thank my parents and my family for all their support and encouragement, which helped me make this book possible.

About the Reviewer

Jakub Glinka is a mathematician, programmer, and data scientist.

He holds a master's degree in applied mathematics from Warsaw University with a specialization in mathematical statistics.

From the beginning of his professional career, he is associated with GfK. His area of expertise ranges from Bayesian modeling to machine learning. He is enthusiastic about new programming languages and currently relying heavily on R and Julia in his professional work.

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Preface

Julia is a programming language that promises both speed and support for extensive data science applications. Apart from the official documentation of the language, and the individual documentations for each package, there is no single resource that combines all of them and provides a detailed guide to carry out machine learning and data science. So, this book aims to solve the problem by being a comprehensive guide to learning data science for a Julia programmer, right from the exploratory analytics part to the visualization part.

What this bo...