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Author: George Root Publisher: ISBN: 9781794681699 Category : Languages : en Pages : 199
Book Description
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.
Author: George Root Publisher: ISBN: 9781794681699 Category : Languages : en Pages : 199
Book Description
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.
Author: Peter K. Austin Publisher: Cambridge University Press ISBN: 113950083X Category : Language Arts & Disciplines Languages : en Pages : 581
Book Description
It is generally agreed that about 7,000 languages are spoken across the world today and at least half may no longer be spoken by the end of this century. This state-of-the-art Handbook examines the reasons behind this dramatic loss of linguistic diversity, why it matters, and what can be done to document and support endangered languages. The volume is relevant not only to researchers in language endangerment, language shift and language death, but to anyone interested in the languages and cultures of the world. It is accessible both to specialists and non-specialists: researchers will find cutting-edge contributions from acknowledged experts in their fields, while students, activists and other interested readers will find a wealth of readable yet thorough and up-to-date information.
Author: Antonello Lobianco Publisher: Apress ISBN: 1484251903 Category : Computers Languages : en Pages : 223
Book Description
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.
Author: Paul D. McNicholas Publisher: CRC Press ISBN: 1351013661 Category : Business & Economics Languages : en Pages : 220
Book Description
"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
Author: Julia Yates Publisher: Routledge ISBN: 1317963482 Category : Business & Economics Languages : en Pages : 249
Book Description
Uniquely combining the latest research into careers with the most up to date coaching approaches, Julia Yates shows how to effectively apply coaching techniques to the world of career support. Demonstrating how coaching research explains practice and how practice benefits from research, The Career Coaching Handbook is accessibly written with a solid evidence-based foundation. Presented in three parts, the book covers developments in theory and research and applies this knowledge to the real world. Part 1, Theories of Career, looks at 21st century career paths, job satisfaction and career changes – both planned and unplanned. Part 2, Career Coaching Approaches, looks at coaching strategies that are applicable to career coaching in particular. Part 3, Coaching into the World of Work, covers specific real-world situations where coaching is beneficial, from job search strategies to CV and interview coaching. Evidence and research is used throughout to demonstrate the most effective strategies for coaching. The Career Coaching Handbook provides an essential introduction for students or practitioners who are interested in developing their own practice, finding new and improved ways to do things and understanding the theories that underpin effective career coaching practice.
Author: Ivo Balbaert Publisher: Packt Publishing Ltd ISBN: 1838824677 Category : Computers Languages : en Pages : 455
Book Description
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.
Author: Julia Herschensohn Publisher: Cambridge University Press ISBN: 9781108733748 Category : Foreign Language Study Languages : en Pages : 0
Book Description
What is language and how can we investigate its acquisition by children or adults? What perspectives exist from which to view acquisition? What internal constraints and external factors shape acquisition? What are the properties of interlanguage systems? This comprehensive 31-chapter handbook is an authoritative survey of second language acquisition (SLA). Its multi-perspective synopsis on recent developments in SLA research provides significant contributions by established experts and widely recognized younger talent. It covers cutting edge and emerging areas of enquiry not treated elsewhere in a single handbook, including third language acquisition, electronic communication, incomplete first language acquisition, alphabetic literacy and SLA, affect and the brain, discourse and identity. Written to be accessible to newcomers as well as experienced scholars of SLA, the Handbook is organised into six thematic sections, each with an editor-written introduction.
Author: C. Addison Stone Publisher: Guilford Publications ISBN: 1462527485 Category : Language Arts & Disciplines Languages : en Pages : 736
Book Description
An acclaimed reference that fills a significant gap in the literature, this volume examines the linkages between spoken and written language development, both typical and atypical. Leading authorities address the impact of specific language-related processes on K-12 literacy learning, with attention to cognitive, neurobiological, sociocultural, and instructional issues. Approaches to achieving optimal learning outcomes with diverse students are reviewed. The volume presents research-based practices for assessing student needs and providing effective instruction in all aspects of literacy: word recognition, reading comprehension, writing, and spelling. New to This Edition *Chapters on digital literacy, disciplinary literacy, and integrative research designs. *Chapters on bilingualism, response to intervention, and English language learners. *Incorporates nearly a decade's worth of empirical and theoretical advances. *Numerous prior edition chapters have been completely rewritten.
Author: Sambit Kumar Dash Publisher: BPB Publications ISBN: 9391030882 Category : Computers Languages : en Pages : 408
Book Description
Build production-ready machine learning and NLP systems using functional programming, development platforms, and cloud deployment. KEY FEATURES ● In-depth explanation and code samples highlighting the features of the Julia language. ● Extensive coverage of the Julia development ecosystem, package management, DevOps environment integration, and performance management tools. ● Exposure to the most important Julia packages that aid in Data and Text Analytics and Deep Learning. DESCRIPTION The Julia Programming language enables data scientists and programmers to create prototypes without sacrificing performance. Nonetheless, skeptics question its readiness for production deployments as a new platform with a 1.0 release in 2018. This book removes these doubts and offers a comprehensive glimpse at the language's use throughout developing and deploying production-ready applications. The first part of the book teaches experienced programmers and scientists about the Julia language features in great detail. The second part consists of gaining hands-on experience with the development environment, debugging, programming guidelines, package management, and cloud deployment strategies. In the final section, readers are introduced to a variety of third-party packages available in the Julia ecosystem for Data Processing, Text Analytics, and developing Deep Learning models. This book provides an extensive overview of the programming language and broadens understanding of the Julia ecosystem. As a result, it assists programmers, scientists, and information architects in selecting Julia for their next production deployments. WHAT YOU WILL LEARN ● Get to know the complete fundamentals of Julia programming. ● Explore Julia development frameworks and how to work with them. ● Dig deeper into the concepts and applications of functional programming. ● Uncover the Julia infrastructure for development, testing, and deployment. ● Learn to practice Julia libraries and the Julia package ecosystem. ● Processing Data, Deep Learning, and Natural Language Processing with Julia. WHO THIS BOOK IS FOR This book is for Data Scientists and application developers who want to learn about Julia application development. No prior Julia knowledge is required but knowing the basics of programming helps understand the objectives of this book. TABLE OF CONTENTS 1. Getting Started 2. Data Types 3. Conditions, Control Flow, and Iterations 4. Functions and Methods 5. Collections 6. Arrays 7. Strings 8. Metaprogramming 9. Standard Libraries Module 2. The Development Environment 10. Programming Guidelines in Julia 11. Performance Management 12. IDE and Debugging 13. Package Management 14. Deployment Module 3. Packages in Julia 15. Data Transformations 16. Text Analytics 17. Deep Learning