[FOX-Ebook]Mastering Julia

Develop your analytical and programming skills further in Julia to solve complex data processing problems

About This Book

• Build statistical models with linear regression and analysis of variance (ANOVA)
• Author your own modules and contribute information to the Julia package system
• Engage yourself in a data science project through the entire cycle of ETL, analytics, and data visualization

Who This Book Is For

This hands-on guide is aimed at practitioners of data science. The book assumes some previous skills with Julia and skills in coding in a scripting language such as Python or R, or a compiled language such as C or Java.

What You Will Learn

• Install and build Julia and configure it with your environment
• Build a data science project through the entire cycle of ETL, analytics, and data visualization
• Understand the type system and principles of multiple dispatch for a better coding experience in Julia
• Interact with data files and data frames to study simple statistics and analytics
• Display graphics and visualizations to carry out modeling and simulation in Julia
• Use Julia to interact with SQL and NoSQL databases
• Work with distributed systems on the Web and in the cloud
• Develop your own packages and contribute to the Julia Community

In Detail

Julia is a well-constructed programming language with fast execution speed, eliminating the classic problem of performing analysis in one language and translating it for performance into a second. This book will help you develop and enhance your programming skills in Julia to solve real-world automation challenges.

This book starts off with a refresher on installing and running Julia on different platforms. Next, you will compare the different ways of working with Julia and explore Julia’s key features in-depth by looking at design and build. You will see how data works using simple statistics and analytics, and discover Julia’s speed, its real strength, which makes it particularly useful in highly intensive computing tasks and observe how Julia can cooperate with external processes in order to enhance graphics and data visualization. Finally, you will look into meta-programming and learn how it adds great power to the language and establish networking and distributed computing with Julia.

Table of Contents

Chapter 1: The Julia Environment
Chapter 2: Developing in Julia
Chapter 3: Types and Dispatch
Chapter 4: Interoperability
Chapter 5: Working with Data
Chapter 6: Scientific Programming
Chapter 7: Graphics
Chapter 8: Databases
Chapter 9: Networking
Chapter 10: Working with Julia