Download or read book Julia Quick Syntax Reference written by Antonello Lobianco and published by Apress. This book was released on 2019-11-11 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: This quick Julia programming language guide is a condensed code and syntax reference to the Julia 1.x programming language, updated with the latest features of the Julia APIs, libraries, and packages. It presents the essential Julia syntax in a well-organized format that can be used as a handy reference. This book provides an introduction that reveals basic Julia structures and syntax; discusses data types, control flow, functions, input/output, exceptions, metaprogramming, performance, and more. Additionally, you'll learn to interface Julia with other programming languages such as R for statistics or Python. You will learn how to use Julia packages for data analysis, numerical optimization and symbolic computation, and how to disseminate your results in dynamic documents or interactive web pages. In this book, the focus is on providing important information as quickly as possible. It is packed with useful information and is a must-have for any Julia programmer. What You Will Learn Set up the software needed to run Julia and your first Hello World exampleWork with types and the different containers that Julia makes available for rapid application developmentUse vectorized, classical loop-based code, logical operators, and blocksExplore Julia functions by looking at arguments, return values, polymorphism, parameters, anonymous functions, and broadcastsBuild custom structures in JuliaInterface Julia with other languages such as C/C++, Python, and RProgram a richer API, modifying the code before it is executed using expressions, symbols, macros, quote blocks, and moreMaximize your code’s performance Who This Book Is For Experienced programmers new to Julia, as well as existing Julia coders new to the now stable Julia version 1.0 release.

Download or read book Julia 1 0 Programming Complete Reference Guide written by Ivo Balbaert and published by Packt Publishing Ltd. This book was released on 2019-05-20 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn dynamic programming with Julia to build apps for data analysis, visualization, machine learning, and the web Key FeaturesLeverage Julia's high speed and efficiency to build fast, efficient applicationsPerform supervised and unsupervised machine learning and time series analysisTackle problems concurrently and in a distributed environmentBook Description Julia offers the high productivity and ease of use of Python and R with the lightning-fast speed of C++. There’s never been a better time to learn this language, thanks to its large-scale adoption across a wide range of domains, including fintech, biotech and artificial intelligence (AI). You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. This Learning Path walks you through two important collection types: arrays and matrices. You’ll be taken through how type conversions and promotions work, and in further chapters you'll study how Julia interacts with operating systems and other languages. You’ll also learn about the use of macros, what makes Julia suitable for numerical and scientific computing, and how to run external programs. Once you have grasped the basics, this Learning Path goes on to how to analyze the Iris dataset using DataFrames. While building a web scraper and a web app, you’ll explore the use of functions, methods, and multiple dispatches. In the final chapters, you'll delve into machine learning, where you'll build a book recommender system. By the end of this Learning Path, you’ll be well versed with Julia and have the skills you need to leverage its high speed and efficiency for your applications. This Learning Path includes content from the following Packt products: Julia 1.0 Programming - Second Edition by Ivo BalbaertJulia Programming Projects by Adrian SalceanuWhat you will learnCreate your own types to extend the built-in type systemVisualize your data in Julia with plotting packagesExplore the use of built-in macros for testing and debuggingIntegrate Julia with other languages such as C, Python, and MATLABAnalyze and manipulate datasets using Julia and DataFramesDevelop and run a web app using Julia and the HTTP packageBuild a recommendation system using supervised machine learningWho this book is for If you are a statistician or data scientist who wants a quick course in the Julia programming language while building big data applications, this Learning Path is for you. Basic knowledge of mathematics and programming is a must.

Download or read book Julia Programming for Operations Research written by Changhyun Kwon and published by Changhyun Kwon. This book was released on 2019-03-03 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Last Updated: December 2020 Based 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

Download or read book Mastering Julia written by Malcolm Sherrington and published by Packt Publishing Ltd. This book was released on 2015-07-22 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Mixed Integer Nonlinear Programming written by Jon Lee and published by Springer Science & Business Media. This book was released on 2011-12-02 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization; but because its scope is so broad, in the most general cases it is hopelessly intractable. Nonetheless, an expanding body of researchers and practitioners — including chemical engineers, operations researchers, industrial engineers, mechanical engineers, economists, statisticians, computer scientists, operations managers, and mathematical programmers — are interested in solving large-scale MINLP instances.

Download or read book Julia Programming Projects written by Adrian Salceanu and published by Packt Publishing Ltd. This book was released on 2018-12-26 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: A step-by-step guide that demonstrates how to build simple-to-advanced applications through examples in Julia Lang 1.x using modern tools Key FeaturesWork with powerful open-source libraries for data wrangling, analysis, and visualizationDevelop full-featured, full-stack web applications Learn to perform supervised and unsupervised machine learning and time series analysis with JuliaBook Description Julia is a new programming language that offers a unique combination of performance and productivity. Its powerful features, friendly syntax, and speed are attracting a growing number of adopters from Python, R, and Matlab, effectively raising the bar for modern general and scientific computing. After six years in the making, Julia has reached version 1.0. Now is the perfect time to learn it, due to its large-scale adoption across a wide range of domains, including fintech, biotech, education, and AI. Beginning with an introduction to the language, Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames. You will explore functions and the type system, methods, and multiple dispatch while building a web scraper and a web app. Next, you'll delve into machine learning, where you'll build a books recommender system. You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database. After metaprogramming, the final chapters will discuss dates and time, time series analysis, visualization, and forecasting. We'll close with package development, documenting, testing and benchmarking. By the end of the book, you will have gained the practical knowledge to build real-world applications in Julia. What you will learnLeverage Julia's strengths, its top packages, and main IDE optionsAnalyze and manipulate datasets using Julia and DataFramesWrite complex code while building real-life Julia applicationsDevelop and run a web app using Julia and the HTTP packageBuild a recommender system using supervised machine learning Perform exploratory data analysis Apply unsupervised machine learning algorithmsPerform time series data analysis, visualization, and forecastingWho this book is for Data scientists, statisticians, business analysts, and developers who are interested in learning how to use Julia to crunch numbers, analyze data and build apps will find this book useful. A basic knowledge of programming is assumed.

Download or read book Think Julia written by Ben Lauwens and published by "O'Reilly Media, Inc.". This book was released on 2019-04-05 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Data Science with Julia written by Paul D. McNicholas and published by CRC Press. This book was released on 2019-01-02 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist."- Professor Charles Bouveyron, INRIA Chair in Data Science, Université Côte d’Azur, Nice, France Julia, an open-source programming language, was created to be as easy to use as languages such as R and Python while also as fast as C and Fortran. An accessible, intuitive, and highly efficient base language with speed that exceeds R and Python, makes Julia a formidable language for data science. Using well known data science methods that will motivate the reader, Data Science with Julia will get readers up to speed on key features of the Julia language and illustrate its facilities for data science and machine learning work. Features: Covers the core components of Julia as well as packages relevant to the input, manipulation and representation of data. Discusses several important topics in data science including supervised and unsupervised learning. Reviews data visualization using the Gadfly package, which was designed to emulate the very popular ggplot2 package in R. Readers will learn how to make many common plots and how to visualize model results. Presents how to optimize Julia code for performance. Will be an ideal source for people who already know R and want to learn how to use Julia (though no previous knowledge of R or any other programming language is required). The advantages of Julia for data science cannot be understated. Besides speed and ease of use, there are already over 1,900 packages available and Julia can interface (either directly or through packages) with libraries written in R, Python, Matlab, C, C++ or Fortran. The book is for senior undergraduates, beginning graduate students, or practicing data scientists who want to learn how to use Julia for data science. "This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist." Professor Charles Bouveyron INRIA Chair in Data Science Université Côte d’Azur, Nice, France

Download or read book Statistics with Julia written by Yoni Nazarathy and published by Springer Nature. This book was released on 2021-09-04 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph uses the Julia language to guide the reader through an exploration of the fundamental concepts of probability and statistics, all with a view of mastering machine learning, data science, and artificial intelligence. The text does not require any prior statistical knowledge and only assumes a basic understanding of programming and mathematical notation. It is accessible to practitioners and researchers in data science, machine learning, bio-statistics, finance, or engineering who may wish to solidify their knowledge of probability and statistics. The book progresses through ten independent chapters starting with an introduction of Julia, and moving through basic probability, distributions, statistical inference, regression analysis, machine learning methods, and the use of Monte Carlo simulation for dynamic stochastic models. Ultimately this text introduces the Julia programming language as a computational tool, uniquely addressing end-users rather than developers. It makes heavy use of over 200 code examples to illustrate dozens of key statistical concepts. The Julia code, written in a simple format with parameters that can be easily modified, is also available for download from the book’s associated GitHub repository online. See what co-creators of the Julia language are saying about the book: Professor Alan Edelman, MIT: With “Statistics with Julia”, Yoni and Hayden have written an easy to read, well organized, modern introduction to statistics. The code may be looked at, and understood on the static pages of a book, or even better, when running live on a computer. Everything you need is here in one nicely written self-contained reference. Dr. Viral Shah, CEO of Julia Computing: Yoni and Hayden provide a modern way to learn statistics with the Julia programming language. This book has been perfected through iteration over several semesters in the classroom. It prepares the reader with two complementary skills - statistical reasoning with hands on experience and working with large datasets through training in Julia.

Download or read book The Julia Language Handbook written by George Root and published by . This book was released on 2019-02-02 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Beginning Julia Programming written by Sandeep Nagar and published by Apress. This book was released on 2017-11-25 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get started with Julia for engineering and numerical computing, especially data science, machine learning, and scientific computing applications. This book explains how Julia provides the functionality, ease-of-use and intuitive syntax of R, Python, MATLAB, SAS, or Stata combined with the speed, capacity, and performance of C, C++, or Java. You’ll learn the OOP principles required to get you started, then how to do basic mathematics with Julia. Other core functionality of Julia that you’ll cover, includes working with complex numbers, rational and irrational numbers, rings, and fields. Beginning Julia Programming takes you beyond these basics to harness Julia’s powerful features for mathematical functions in Julia, arrays for matrix operations, plotting, and more. Along the way, you also learn how to manage strings, write functions, work with control flows, and carry out I/O to implement and leverage the mathematics needed for your data science and analysis projects. "Julia walks like Python and runs like C". This phrase explains why Julia is quickly growing as the most favored option for data analytics and numerical computation. After reading and using this book, you'll have the essential knowledge and skills to build your first Julia-based application. What You'll Learn Obtain core skills in Julia Apply Julia in engineering and science applications Work with mathematical functions in Julia Use arrays, strings, functions, control flow, and I/O in Julia Carry out plotting and display basic graphics Who This Book Is For Those who are new to Julia; experienced users may also find this helpful as a reference.

Download or read book Nineteen Eighty Four written by George Orwell and published by epubli. This book was released on 2021-01-09 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Nineteen Eighty-Four: A Novel", often published as "1984", is a dystopian social science fiction novel by English novelist George Orwell. It was published on 8 June 1949 by Secker & Warburg as Orwell's ninth and final book completed in his lifetime. Thematically, "Nineteen Eighty-Four" centres on the consequences of totalitarianism, mass surveillance, and repressive regimentation of persons and behaviours within society. Orwell, himself a democratic socialist, modelled the authoritarian government in the novel after Stalinist Russia. More broadly, the novel examines the role of truth and facts within politics and the ways in which they are manipulated. The story takes place in an imagined future, the year 1984, when much of the world has fallen victim to perpetual war, omnipresent government surveillance, historical negationism, and propaganda. Great Britain, known as Airstrip One, has become a province of a totalitarian superstate named Oceania that is ruled by the Party who employ the Thought Police to persecute individuality and independent thinking. Big Brother, the leader of the Party, enjoys an intense cult of personality despite the fact that he may not even exist. The protagonist, Winston Smith, is a diligent and skillful rank-and-file worker and Outer Party member who secretly hates the Party and dreams of rebellion. He enters into a forbidden relationship with a colleague, Julia, and starts to remember what life was like before the Party came to power.

Download or read book Three Junes written by Julia Glass and published by Anchor. This book was released on 2002-09-03 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: NATIONAL BOOK AWARD WINNER • NATIONAL BESTSELLER • An astonishing novel that traces the lives of a Scottish family over a decade as they confront the joys and longings, fulfillments and betrayals of love in all its guises. In June of 1989 Paul McLeod, a newspaper publisher and recent widower, travels to Greece, where he falls for a young American artist and reflects on the complicated truth about his marriage.... Six years later, again in June, Paul’s death draws his three grown sons and their families back to their ancestral home. Fenno, the eldest, a wry, introspective gay man, narrates the events of this unforeseen reunion. Far from his straitlaced expatriate life as a bookseller in Greenwich Village, Fenno is stunned by a series of revelations that threaten his carefully crafted defenses.... Four years farther on, in yet another June, a chance meeting on the Long Island shore brings Fenno together with Fern Olitsky, the artist who once captivated his father. Now pregnant, Fern must weigh her guilt about the past against her wishes for the future and decide what family means to her. In prose rich with compassion and wit, Three Junes paints a haunting portrait of love’s redemptive powers.

Download or read book Carpenter s Complete Guide to the SAS Macro Language Third Edition written by Art Carpenter and published by SAS Institute. This book was released on 2016-08-25 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing both a compendium of reusable and adaptable code, and opportunities for deepening your understanding and growing as a SAS programmer, this pragmatic, example-driven reference offers nearly 400 ready-to-use macros, macro functions, and macro tools that enable you to convert SAS code to macros, define macro variables, and more. --

Download or read book R Quick Syntax Reference written by Margot Tollefson and published by Apress. This book was released on 2014-04-30 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: The R Quick Syntax Reference is a handy reference book detailing the intricacies of the R language. Not only is R a free, open-source tool, R is powerful, flexible, and has state of the art statistical techniques available. With the many details which must be correct when using any language, however, the R Quick Syntax Reference makes using R easier. Starting with the basic structure of R, the book takes you on a journey through the terminology used in R and the syntax required to make R work. You will find looking up the correct form for an expression quick and easy. With a copy of the R Quick Syntax Reference in hand, you will find that are able to use the multitude of functions available to the R user and are even able to write your own functions to explore and analyze data. Takes you through learning R, from download to statistical analysis. Clears the confusion around object types and how to use and convert the types. Tells you how to search for statistical techniques using the R help pages.

Download or read book Python for Scientists written by John M. Stewart and published by Cambridge University Press. This book was released on 2017-07-20 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scientific Python is taught from scratch in this book via copious, downloadable, useful and adaptable code snippets. Everything the working scientist needs to know is covered, quickly providing researchers and research students with the skills to start using Python effectively.

Download or read book R Markdown written by Yihui Xie and published by CRC Press. This book was released on 2018-07-27 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: R Markdown: The Definitive Guide is the first official book authored by the core R Markdown developers that provides a comprehensive and accurate reference to the R Markdown ecosystem. With R Markdown, you can easily create reproducible data analysis reports, presentations, dashboards, interactive applications, books, dissertations, websites, and journal articles, while enjoying the simplicity of Markdown and the great power of R and other languages. In this book, you will learn Basics: Syntax of Markdown and R code chunks, how to generate figures and tables, and how to use other computing languages Built-in output formats of R Markdown: PDF/HTML/Word/RTF/Markdown documents and ioslides/Slidy/Beamer/PowerPoint presentations Extensions and applications: Dashboards, Tufte handouts, xaringan/reveal.js presentations, websites, books, journal articles, and interactive tutorials Advanced topics: Parameterized reports, HTML widgets, document templates, custom output formats, and Shiny documents. Yihui Xie is a software engineer at RStudio. He has authored and co-authored several R packages, including knitr, rmarkdown, bookdown, blogdown, shiny, xaringan, and animation. He has published three other books, Dynamic Documents with R and knitr, bookdown: Authoring Books and Technical Documents with R Markdown, and blogdown: Creating Websites with R Markdown. J.J. Allaire is the founder of RStudio and the creator of the RStudio IDE. He is an author of several packages in the R Markdown ecosystem including rmarkdown, flexdashboard, learnr, and radix. Garrett Grolemund is the co-author of R for Data Science and author of Hands-On Programming with R. He wrote the lubridate R package and works for RStudio as an advocate who trains engineers to do data science with R and the Tidyverse.