Tackle the Contemporary Challenges of Programming and Data Science with Julia About This Book * 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. Who This Book Is For This book will appeal to Julia programmers who are practitioners of data science and would like to take their development skills to the next level. What You Will Learn * Install and build Julia and configure it with your environment *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 *Explore the best packages for Machine Learning with Julia. *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. If you want to develop and enhance your programming skills in Julia to solve real-world automation challenges, then this book is for you. The book starts off with a refresher to Julia and talks about the latest improvements and features in 1.0. 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. You will further explore and see how Julia can cooperate with external processes in order to enhance graphics and data visualization. The book will then show you the GPU support and explore the various packages for Machine Learning in Julia. 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.