Key Features

• Build statistical models with linear regression and analysis of variance (ANOVA)
• Create your own modules and contribute to the Julia package system
• Complete an extensive data science project through the entire cycle from ETL to analytics and data visualization

Book Description

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.

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

About the Author

Malcolm Sherrington has been working in computing for over 35 years. He currently runs his own company in the finance sector, and is particularly interested in High Performance Computing and applications of GPUs and parallelism. Malcolm is also the organizer of the London Julia User Group, and co-organizer of the UK High Performance Computing and the financial engineers and Quant London meetup groups.

Table of Contents

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