In our guide of the day we’ll cover the best books to learn Julia Programming Language. Julia is an open source, high-level, high-performance dynamic language for technical computing. This programming language was designed from the beginning for excellence performance. It is a general-purpose language fit for numerical analysis and computational science as well as web programming and scripting.

Julia programs compile to efficient native code for multiple platforms via LLVM. The project has over 1,000 active contributors. Julia is a dynamically typed language with a clean syntax which feels like a scripting language with good support for interactive use cases.

Best Books To Learn Julia Programming Language

The next section will cover the top recommended books to learn Julia programming language in the new year. We’ve not ranked the books in any particular order and you can pick the one that suites your learning objectives and timelines.

1. Think Julia: How to Think Like a Computer Scientist

This hands-on oriented book walk you through programming with Julia is step at a time manner. It begs with basic concepts of programming before moving on to more advanced capabilities, such as creating new types and multiple dispatch.

Each chapter has some exercises that makes you try out programming concepts as progress with learning. This book os perfect for students at the high school or college level as well as self-learners and professionals who need to learn programming basics.

Books details:

  • Start with the basics, including language syntax and semantics
  • Get a clear definition of each programming concept
  • Learn about values, variables, statements, functions, and data structures in a logical progression
  • Discover how to work with files and databases
  • Understand types, methods, and multiple dispatch
  • Use debugging techniques to fix syntax, runtime, and semantic errors
  • Explore interface design and data structures through case studies

Think Julia: How to Think Like a Computer Scientist

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2. Hands-On Design Patterns and Best Practices with Julia

The books starts with an overview of design patterns and best practices in general application design. You’ll get to learn about fundamental features of Julia programming language such as data types, modules, functions&interfaces, and metaprogramming.

The focus is to get you to speed with modern Julia design patterns for building large-scale applications with a focus on reusability, performance, robustness, and maintainability. The book also covers anti-patterns and how to avoid common mistakes and pitfalls in development. There are tons of use cases and examples, such as how expert Julia developers use design patterns in their open source packages.

What you will learn

  • Master the Julia language features that are key to developing large-scale software applications
  • Discover design patterns to improve overall application architecture and design
  • Develop reusable programs that are modular, extendable, performant, and easy to maintain
  • Weigh up the pros and cons of using different design patterns for use cases
  • Explore methods for transitioning from object-oriented programming to using equivalent or more advanced Julia techniques

Hands-On Design Patterns and Best Practices with Julia: Proven solutions to common problems in software design for Julia 1.x

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3. Julia Programming for Operations Research

Changhyun Kwon, the author of the books it a professor in the field of operations research, and his daily activities involve building models of mathematical optimization, developing algorithms for solving the problems, implementing those algorithms using computer programming languages, experimenting with data, etc.

This book will be very useful to anyone who needs to use Julia in research work as the author wrote it to serve his interests around the said areas. If you’re a student or professional in operations research and related areas such as industrial engineering, management science, transportation engineering, economics, and regional science, this book is for you.

Julia Programming for Operations Research

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4. Tanmay Teaches Julia for Beginners: A Springboard to Machine Learning for All Ages

This is an engaging piece of work with step by step guides on how to build custom programs using Julia. It has been written by Tanmay Bakshi who has more than 15 years of experience in technology and programming.

The book is presented in an accessible style that makes learning easy and enjoyable. Tanmay explains the basics of Julia programming and takes a look at cutting-edge machine learning applications. You will also discover how to interface your Julia apps with code written in Python.

By the end of the book you’ll have learn to:

  • Set up and configure your Julia environment
  • Get up and running writing your own Julia apps
  • Define variables and use them in your programs
  • Use conditions, iterations, for-loops, and while-loops
  • Create, go through, and modify arrays
  • Build an app to manage things you lend and get back from your friends
  • Create and utilize dictionaries
  • Simplify maintenance of your code using functions
  • Apply functions on arrays and use functions recursively and generically
  • Understand and program basic machine learning apps

Tanmay Teaches Julia for Beginners: A Springboard to Machine Learning for All Ages

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5. Julia Programming Projects

The Julia Programming Projects is created for Business Analysts, Data scientists, people in statistics field, and developers interested in mastering how Julia can be used to analyze data and build applications. It begins with an introduction to the Julia language, then divest to illustrate how to analyze the Iris dataset using DataFrames, functions and the type system, methods, and multiple dispatch while building a web scraper and a web application.

By the end of the book, you will have gained the practical knowledge to build real-world applications in Julia.

  • Leverage Julia’s strengths, its top packages, and main IDE options
  • Analyze and manipulate datasets using Julia and DataFrames
  • Write complex code while building real-life Julia applications
  • Develop and run a web app using Julia and the HTTP package
  • Build a recommender system using supervised machine learning
  • Perform exploratory data analysis
  • Apply unsupervised machine learning algorithms
  • Perform time series data analysis, visualization, and forecasting

Julia Programming Projects: Learn Julia 1.x by building apps for data analysis, visualization, machine learning, and the web

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