Mastering Julia. Enhance your analytical and programming skills for data modeling and processing with Julia
2nd edition

Julia is a well-constructed programming language that was designed for fast execution speeds by using just-in-time LLVM compilation techniques, thus eliminating the classic problem of performing analysis in one language and translating it for performance in a second language. This book is a primer on Julia's approach to a wide variety of topics such as scientific computing, statistics, machine learning, simulation, graphics, and distributed computing.
Starting off with a refresher on installing and running Julia on different platforms, you'll quickly get to grips with the core concepts and delve into a discussion on how to use Julia with various code editors and interactive development environments (IDEs). As you progress, you'll see how data works through simple statistics and analytics and discover Julia's speed, its real strength, which makes it particularly useful in highly intensive computing tasks.
You'll also observe how Julia can cooperate with external processes to enhance graphics and data visualizations. Finally, you will explore metaprogramming and learn how it adds great power to the language and establishes networking and distributed computing with Julia. By the end of this book, you'll be confident in using Julia as part of your existing skill set.

What you will learn : Get to grips with Julia's type system, multiple dispatch, metaprogramming, and macro development. Interact with data files, tables, data frames, SQL, and NoSQL databases. Delve into statistical analytics, linear programming, and optimization problems. Create graphics and visualizations to enhance modeling and simulation in Julia. Understand Julia's main approaches to machine learning, Bayesian analysis, and Al.