Learn to use Julia as a tool for research, and solve problems of genuine interest—like modeling the course of a pandemic—in this practical, hands-on introduction to the language.The Julia programming language is acclaimed in scientific circles for its unparalleled ease, interactivity, and speed. Practical Julia is a comprehensive introduction to the language, making it accessible even if you’re new to programming.Dive in with a thorough guide to Julia’s syntax, data types, and best practices, then transition to craft solutions for challenges in physics, statistics, biology, mathematics, scientific machine learning, and more. Whether you’re solving computational problems, visualizing data, writing simulations, or developing specialized tools, Practical Julia will show you how.As you work through the book, you’ll:• Use comprehensions and generators, higher-level functions, array initialization and manipulation, and perform operations on Unicode text• Create new syntax and generate code with metaprogramming and macros, and control the error system to manipulate program execution• Visualize everything from mathematical constructs and experimental designs to algorithm flowcharts• Elevate performance using Julia’s unique type system with multiple dispatch• Delve into scientific packages tailored for diverse fields like fluid dynamics, agent-based modeling, and image processingWhether your interest is in scientific research, statistics, mathematics, or just the fun of programming with Julia, Practical Julia will have you writing high-performance code that can do real work in no time.Online Resources: Ready-to-run code samples, illustrations, and supplemental animations available at https://julia.lee-phillips.org.

Learn the awesome Julia programming language by building fun projects like a rocket launcher, a password keeper, and a battle simulator.Julia as a Second Language covers:Data types like numbers, strings, arrays, and dictionaries Immediate feedback with Julia’s read-evaluate-print-loop (REPL) Simplify code interactions with multiple dispatch Sharing code using modules and packages Object-oriented and functional programming stylesJulia as a Second Language introduces Julia to readers with a beginning-level knowledge of another language like Python or JavaScript. You’ll learn by coding engaging hands-on projects that encourage you to apply what you’re learning immediately. Don’t be put off by Julia’s reputation as a scientific programming language—there’s no data science or numerical computing knowledge required. You can get started with what you learned in high school math classes.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyOriginally designed for high-performance data science, Julia has become an awesome general purpose programming language. It offers developer-friendly features like garbage collection, dynamic typing, and a flexible approach to concurrency and distributed computing. It is the perfect mix of simplicity, flexibility and performance.About the BookJulia as a Second Language introduces Julia by building on your existing programming knowledge. You’ll see Julia in action as you create a series of interesting projects that guide you from Julia’s basic syntax through its advanced features. Master types and data structures as you model a rocket launch. Use dictionaries to interpret Roman numerals. Use Julia’s unique multiple dispatch feature to send knights and archers into a simulated battle. Along the way, you’ll even compare the object-oriented and functional programming styles–Julia supports both!What’s InsideData types like numbers, strings, arrays, and dictionaries Immediate feedback with Julia’s read-evaluate-print-loop (REPL) Simplify code interactions with multiple dispatch Share code using modules and packagesAbout the ReaderFor readers comfortable with another programming language like Python, JavaScript, or C#.About the AuthorErik Engheim is a writer, conference speaker, video course author, and software developer.Table of ContentsPART 1 - BASICS1 Why Julia?2 Julia as a calculator3 Control flow4 Julia as a spreadsheet5 Working with text6 Storing data in dictionariesPART 2 - TYPES7 Understanding types8 Building a rocket9 Conversion and promotion10 Representing unknown valuesPART 3 - COLLECTIONS11 Working with strings12 Understanding Julia collections13 Working with sets14 Working with vectors and matricesPART 4 - SOFTWARE ENGINEERING15 Functional programming in Julia16 Organizing and modularizing your codePART 5 - GOING IN DEPTH17 Input and output18 Defining parametric types

Targeted at middle and high school programmers, this book aims to explain basic computer science concepts while teaching the Julia programming language. As a fast and productive high level language, Julia is ideal for beginner programmers. The learning curve for programming can be quite steep and this book aims to ease this transition by encouraging practise and gradually introducing more complex concepts. The book contains 50 programming challenges that encourages the reader to write their own programs. The solutions to all challenges are given at the end of the book. This book will make readers comfortable with using computers to solve any problems, and leave them well prepared for more significant programming in their maths, science or computer science courses at college. After finishing the exercises in this book, the reader should feel more familiar with: •Loops and conditionals •Structuring code with functions •Reading and writing files •Installing and using packages •Sorting and searching •Simple Statistics and Plotting. Originally written in Python as "The Little Book of Algorithms 2.0" by William Lau, this version updates the text to use Julia. With a foreword by Jeff Bezanson, co-creator of the Julia programming language.

[from the Preface] This introductory textbook in undergraduate probability emphasizes the inseparability between data (computing) and probability (theory) in our time. It examines the motivation, intuition, and implication of the probabilistic tools used in science and engineering: Motivation: In the ocean of mathematical definitions, theorems, and equations, why should we spend our time on this particular topic but not another? Intuition: When going through the deviations, is there a geometric interpretation or physics beyond those equations? Implication: After we have learned a topic, what new problems can we solve?

Tackle the Contemporary Challenges of Programming and Data Science with JuliaKey FeaturesBuild statistical models with linear regression and analysis of variance (ANOVA)Create your own modules and contribute to the Julia package systemComplete an extensive data science project through the entire cycle from ETL to analytics and data visualization.Book DescriptionJulia 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.What you will learnInstall and build Julia and configure it with your environmentUnderstand the type system and principles of multiple dispatch for a better coding experience in JuliaInteract with data files and data frames to study simple statistics and analyticsDisplay graphics and visualizations to carry out modeling and simulation in JuliaUse Julia to interact with SQL and NoSQL databasesExplore the best packages for Machine Learning with Julia.Work with distributed systems on the Web and in the cloudDevelop your own packages and contribute to the Julia CommunityWho This Book Is ForThis book will appeal to Julia programmers who are practitioners of data science and would like to take their development skills to the next level.

Master core data analysis skills using Julia. Interesting hands-on projects guide you through time series data, predictive models, popularity ranking, and more.In Julia for Data Analysis you will learn how to:Read and write data in various formatsWork with tabular data, including subsetting, grouping, and transformingVisualize your dataBuild predictive modelsCreate data processing pipelinesCreate web services sharing results of data analysisWrite readable and efficient Julia programsJulia was designed for the unique needs of data scientists: it's expressive and easy-to-use whilst also delivering super-fast code execution. Julia for Data Analysis shows you how to take full advantage of this amazing language to read, write, transform, analyze, and visualize data—everything you need for an effective data pipeline. It’s written by Bogumil Kaminski, one of the top contributors to Julia, #1 Julia answerer on StackOverflow, and a lead developer of Julia’s core data package DataFrames.jl. Its engaging hands-on projects get you into the action quickly. Plus, you’ll even be able to turn your new Julia skills to general purpose programming!Foreword by Viral Shah.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the technologyJulia is a great language for data analysis. It’s easy to learn, fast, and it works well for everything from one-off calculations to full-on data processing pipelines. Whether you’re looking for a better way to crunch everyday business data or you’re just starting your data science journey, learning Julia will give you a valuable skill.About the bookJulia for Data Analysis teaches you how to handle core data analysis tasks with the Julia programming language. You’ll start by reviewing language fundamentals as you practice techniques for data transformation, visualizations, and more. Then, you’ll master essential data analysis skills through engaging examples like examining currency exchange, interpreting time series data, and even exploring chess puzzles. Along the way, you’ll learn to easily transfer existing data pipelines to Julia.What's insideRead and write data in various formatsWork with tabular data, including subsetting, grouping, and transformingCreate data processing pipelinesCreate web services sharing results of data analysisWrite readable and efficient Julia programsAbout the readerFor data scientists familiar with Python or R. No experience with Julia required.About the authorBogumil Kaminski iis one of the lead developers of DataFrames.jl—the core package for data manipulation in the Julia ecosystem. He has over 20 years of experience delivering data science projects.Table of Contents1 IntroductionPART 1 ESSENTIAL JULIA SKILLS2 Getting started with Julia3 Julia’s support for scaling projects4 Working with collections in Julia5 Advanced topics on handling collections6 Working with strings7 Handling time-series data and missing valuesPART 2 TOOLBOX FOR DATA ANALYSIS8 First steps with data frames9 Getting data from a data frame10 Creating data frame objects11 Converting and grouping data frames12 Mutating and transforming data frames13 Advanced transformations of data frames14 Creating web services for sharing data analysis results

Get a practical overview of web development in Julia and learn how to build MVC applications with a REST API, and an interactive data dashboard using the Genie web frameworkKey Features: A tutorial on web development from Julia expert, Ivo Balbaert and the creator of the Genie framework, Adrian Salceanu A step-by-step approach to building a complete web app with the Genie framework Develop secure and fast web apps using server-side development on JuliaBook Description:Julia's high-performance and scalability characteristics and its extensive number of packages for visualizing data make it an excellent fit for developing web apps, web services, and web dashboards. The two parts of this book provide complete coverage to build your skills in web development.First, you'll refresh your knowledge of the main concepts in Julia that will further be used in web development. Then, you'll use Julia's standard web packages and examine how the building blocks of the web such as TCP-IP, web sockets, HTTP protocol, and so on are implemented in Julia's standard library. Each topic is discussed and developed into code that you can apply in new projects, from static websites to dashboards. You'll also understand how to choose the right Julia framework for a project. The second part of the book talks about the Genie framework. You'll learn how to build a traditional to do app following the MVC design pattern. Next, you'll add a REST API to this project, including testing and documentation. Later, you'll explore the various ways of deploying an app in production, including authentication functionality. Finally, you'll work on an interactive data dashboard, making various chart types and filters.By the end of this book, you'll be able to build interactive web solutions on a large scale with a Julia-based web framework.What You Will Learn: Understand how to make a web server with HTTP.jl and work with JSON data over the web Discover how to build a static website with the Franklin framework Explore Julia web development frameworks and work with them Uncover the Julia infrastructure for development, testing, package management, and deployment Develop an MVC web app with the Genie framework Understand how to add a REST API to a web app Create an interactive data dashboard with charts and filters Test, document, and deploy maintainable web applications using JuliaWho this book is for:This book is for beginner to intermediate-level Julia programmers who want to enhance their skills in designing and developing large-scale web applications. The book helps you adopt Genie without any prior experience with the framework. Julia programming experience and a beginner-level understanding of web development concepts are required.

If you’re just learning how to program, Julia is an excellent JIT-compiled, dynamically typed language with a clean syntax. This hands-on guide uses Julia 1.0 to walk you through programming one step at a time, beginning with basic programming concepts before moving on to more advanced capabilities, such as creating new types and multiple dispatch.Designed from the beginning for high performance, Julia is a general-purpose language ideal for not only numerical analysis and computational science but also web programming and scripting. Through exercises in each chapter, you’ll try out programming concepts as you learn them. Think Julia is perfect for students at the high school or college level as well as self-learners and professionals who need to learn programming basics. 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

Key Features An in-depth exploration of Julia's growing ecosystem of packages by building 4 exciting projects Work with the most powerful open-source libraries for machine learning, data wrangling, and data visualization. Learn to perform supervised learning, unsupervised learning as well as time series analysis with Julia. Book DescriptionJulia is a young programming language that offers a unique combination of performance and productivity that promises to change scientific computing and programming. It also puts performance center stage, achieving C-like execution speed and excellent applications in multi-core, GPU, and cloud computing. After six years in development as an Open Source project, Julia is now ready to take the stage with the release of v1.0. Follow through "Julia v1.0 By Example" for an encompassing exploration of the language by means of progressively engaging examples.Build practical knowledge and use Julia and its most popular packages to address data science problems and handle generic programming tasks. Beginning with an introduction to the language and its syntax, the book will go on to building the first project where you will learn to analyze and manipulate the Iris dataset using Julia. Then we will explore functions and Julia's type system to build a complex web scraping project. Further, you'll dive into more advanced stuff like supervised machine learning where you'll build a recommender system for a dating website. For the final project, you will go deeper, learning about unsupervised learning, time series, statistics functions as well as visualization with Gadfly and Vega. By the end of the book, you would have gained the practical knowledge, enough to help you build statistical models and projects in Julia. What you will learn Leverage Julia Lang's features, and work with packages. Analyze and manipulate dataset using Julia Write complex code while building a real-life Julia application Utilize functions, user defined types and various control flow available with Julia. Develop and execute a web app using Julia and HTTP.Server Build a supervised machine learning system with Julia using available packages Explore unsupervised machine learning algorithms for data analytics

Design and develop high-performance programs in Julia 1.0 Key Features Learn the characteristics of high-performance Julia code Use the power of the GPU to write efficient numerical code Speed up your computation with the help of newly introduced shared memory multi-threading in Julia 1.0 Book DescriptionJulia is a high-level, high-performance dynamic programming language for numerical computing. If you want to understand how to avoid bottlenecks and design your programs for the highest possible performance, then this book is for you.The book starts with how Julia uses type information to achieve its performance goals, and how to use multiple dispatches to help the compiler emit high-performance machine code. After that, you will learn how to analyze Julia programs and identify issues with time and memory consumption. We teach you how to use Julia's typing facilities accurately to write high-performance code and describe how the Julia compiler uses type information to create fast machine code. Moving ahead, you'll master design constraints and learn how to use the power of the GPU in your Julia code and compile Julia code directly to the GPU. Then, you'll learn how tasks and asynchronous IO help you create responsive programs and how to use shared memory multithreading in Julia. Toward the end, you will get a flavor of Julia's distributed computing capabilities and how to run Julia programs on a large distributed cluster.By the end of this book, you will have the ability to build large-scale, high-performance Julia applications, design systems with a focus on speed, and improve the performance of existing programs. What you will learn Understand how Julia code is transformed into machine code Measure the time and memory taken by Julia programs Create fast machine code using Julia's type information Define and call functions without compromising Julia's performance Accelerate your code via the GPU Use tasks and asynchronous IO for responsive programs Run Julia programs on large distributed clusters Who this book is forThis book is for beginners and intermediate Julia programmers who are interested in high-performance technical programming. A basic knowledge of Julia programming is assumed. Table of Contents Julia is Fast Analyzing Performance Type, Type Inference, and Stability Making Fast Function Calls Fast Numbers Using Arrays Accelerating code with the GPU Concurrent programming with Tasks Threads Distributed Computing with Julia

Design and develop high-performance, reusable, and maintainable applications using traditional and modern Julia patterns with this comprehensive guide Key Features Explore useful design patterns along with object-oriented programming in Julia 1.0 Implement macros and metaprogramming techniques to make your code faster, concise, and efficient Develop the skills necessary to implement design patterns for creating robust and maintainable applications Book DescriptionDesign patterns are fundamental techniques for developing reusable and maintainable code. They provide a set of proven solutions that allow developers to solve problems in software development quickly. This book will demonstrate how to leverage design patterns with real-world applications.Starting with an overview of design patterns and best practices in application design, you'll learn about some of the most fundamental Julia features such as modules, data types, functions/interfaces, and metaprogramming. You'll then get to grips with the modern Julia design patterns for building large-scale applications with a focus on performance, reusability, robustness, and maintainability. The book also covers anti-patterns and how to avoid common mistakes and pitfalls in development. You'll see how traditional object-oriented patterns can be implemented differently and more effectively in Julia. Finally, you'll explore various use cases and examples, such as how expert Julia developers use design patterns in their open source packages.By the end of this Julia programming book, you'll have learned methods to improve software design, extensibility, and reusability, and be able to use design patterns efficiently to overcome common challenges in software development. 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 Who this book is forThis book is for beginner to intermediate-level Julia programmers who want to enhance their skills in designing and developing large-scale applications. Table of Contents Design Patterns and Related Principles Modules, Packages, and Data Type Concepts Designing Functions and Interfaces Macros and Meta Programming Techniques Reusability Patterns Performance Patterns Maintainability Patterns Robustness Patterns Miscellaneous Patterns Anti-Patterns Object Oriented Traditional Patterns Inheritance and Variance

Enter the exciting world of Julia, a high-performance language for technical computing Key Features Leverage Julia's high speed and efficiency for your applications Work with Julia in a multi-core, distributed, and networked environment Apply Julia to tackle problems concurrently and in a distributed environment Book DescriptionThe release of Julia 1.0 is now ready to change the technical world by combining the high productivity and ease of use of Python and R with the lightning-fast speed of C++. Julia 1.0 programming gives you a head start in tackling your numerical and data problems. You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. With the help of practical examples, this book walks you through two important collection types: arrays and matrices. In addition to this, you will be taken through how type conversions and promotions work.In the course of the book, you will be introduced to the homo-iconicity and metaprogramming concepts in Julia. You will understand how Julia provides different ways to interact with an operating system, as well as other languages, and then you'll discover what macros are. Once you have grasped the basics, you’ll study what makes Julia suitable for numerical and scientific computing, and learn about the features provided by Julia. By the end of this book, you will also have learned how to run external programs.This book covers all you need to know about Julia in order to leverage its high speed and efficiency for your applications. What you will learn Set up your Julia environment to achieve high productivity Create your own types to extend the built-in type system Visualize your data in Julia with plotting packages Explore the use of built-in macros for testing and debugging, among other uses Apply Julia to tackle problems concurrently Integrate Julia with other languages such as C, Python, and MATLAB Who this book is forJulia 1.0 Programming is for you if you are a statistician or data scientist who wants a crash course in the Julia programming language while building big data applications. A basic knowledge of mathematics is needed to understand the various methods that are used or created during the course of the book to exploit the capabilities that Julia is designed with. Table of Contents Installing the Julia Platform Variables, Types, and Operations Functions Control Flow Collection Types More on Types, Methods, and Modules Metaprogramming in Julia I/O, Networking, and Parallel Computing Running External Programs The Standard Library and Packages

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.A quick guide to start writing your own fun and useful Julia apps―no prior experience required!This engaging guide shows, step by step, how to build custom programs using Julia, the open-source, intuitive scripting language. Written by 15-year-old technology phenom Tanmay Bakshi, the book is presented in an accessible style that makes learning easy and enjoyable. Tanmay Teaches Julia for Beginners: A Springboard to Machine Learning for All Ages clearly 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.Inside, you’ll 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

If you are new to Julia and want a reference that describes how to install and use Julia, this is the book you want. Many of the other Julia books available describe previous versions with examples that no longer work. The “Julia Handbook” is current as of Julia v1.02 and every example, of which there are dozens, has been tested and they all work.You will learn how to install and use the Julia REPL mode and the Jupyter Notebook mode to create and test your code. Other topics include:Data TypesFunctions and PackagesTuplesData ArraysData FramesData StructuresFlow ControlLoops and IterationInput / Output - formatted printing - writing and reading data filesLine and Scatter PlotsOther Plot TypesRandom NumbersOptimization Using Optim and JuMPThis is the book I wanted to buy when I started learning Julia but I had to write it myself to get all of the detail and up-to-date information I wanted. If you are just learning Julia you will find this to be a useful guide. If you are already using Julia you will find this to be an excellent reference book to remind you of some obscure Julia syntax.

Last Updated: December 2020Based on Julia v1.3+ and JuMP v0.21+The main motivation of writing this book was to help the author himself. He is 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. Three languages are involved: human language, mathematical language, and computer language. His team of students need to go over three different languages, which requires "translation" among the three languages. As this book was written to teach his research group how to translate, this book will also be useful for anyone who needs to learn how to translate in a similar situation.The Julia Language is as fast as C, as convenient as MATLAB, and as general as Python with a flexible algebraic modeling language for mathematical optimization problems. With the great support from Julia developers, especially the developers of the JuMP—Julia for Mathematical Programming—package, Julia makes a perfect tool for students and professionals in operations research and related areas such as industrial engineering, management science, transportation engineering, economics, and regional science.For more information, visit: http://www.chkwon.net/julia