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Learning Julia

Author: Leah Hanson
Publisher: O'Reilly Media
ISBN: 9781491903605
Size: 35.11 MB
Format: PDF, ePub, Docs
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This book will walk you through the Julia language. First it will use examples to show off different sides of Julia: writing a simple, fast simulation; plotting data; and defining a new numeric type and associated arithmetic operators. The rest of the chapters will each focus on a specific part of Julia (or its packages), demonstrating how to use them through a series of code examples.

Julia High Performance

Author: Avik Sengupta
Publisher: Packt Publishing Ltd
ISBN: 1785887823
Size: 19.57 MB
Format: PDF, ePub, Docs
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Design and develop high performing programs with Julia About This Book Learn to code high reliability and high performance programs Stand out from the crowd by developing code that runs faster than your peers' codes This book is intended for developers who are interested in high performance technical programming. Who This Book Is For This book is for beginner and intermediate Julia programmers who are interested in high performance technical computing. You will have a basic familiarity with Julia syntax, and have written some small programs in the language. What You Will Learn Discover the secrets behind Julia's speed Get a sense of the possibilities and limitations of Julia's performance Analyze the performance of Julia programs 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 Understand number types in Julia Use Julia arrays to write high performance code Get an overview of Julia's distributed computing capabilities In Detail Julia is a high performance, high-level dynamic language designed to address the requirements of high-level numerical and scientific computing. Julia brings solutions to the complexities faced by developers while developing elegant and high performing code. Julia High Performance will take you on a journey to understand the performance characteristics of your Julia programs, and enables you to utilize the promise of near C levels of performance in Julia. You will learn to analyze and measure the performance of Julia code, understand how to avoid bottlenecks, and design your program for the highest possible performance. In this book, you will also see how Julia uses type information to achieve its performance goals, and how to use multuple dispatch to help the compiler to emit high performance machine code. Numbers and their arrays are obviously the key structures in scientific computing – you will see how Julia's design makes them fast. The last chapter will give you a taste of Julia's distributed computing capabilities. Style and approach This is a hands-on manual that will give you good explanations about the important concepts related to Julia programming.

Big Data And Social Science

Author: Ian Foster
Publisher: CRC Press
ISBN: 1498751431
Size: 20.31 MB
Format: PDF, Docs
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Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.

Mastering Julia

Author: Malcolm Sherrington
Publisher: Packt Publishing Ltd
ISBN: 1783553324
Size: 71.55 MB
Format: PDF, ePub, Docs
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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.

Julia For Data Science

Author: Zacharias Voulgaris, PhD
Publisher: Technics Publications
ISBN: 1634621328
Size: 13.74 MB
Format: PDF, Docs
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Master how to use the Julia language to solve business critical data science challenges. After covering the importance of Julia to the data science community and several essential data science principles, we start with the basics including how to install Julia and its powerful libraries. Many examples are provided as we illustrate how to leverage each Julia command, dataset, and function. Specialized script packages are introduced and described. Hands-on problems representative of those commonly encountered throughout the data science pipeline are provided, and we guide you in the use of Julia in solving them using published datasets. Many of these scenarios make use of existing packages and built-in functions, as we cover: 1. 1. An overview of the data science pipeline along with an example illustrating the key points, implemented in Julia 2. 2. Options for Julia IDEs 3. 3. Programming structures and functions 4. 4. Engineering tasks, such as importing, cleaning, formatting and storing data, as well as performing data preprocessing 5. 5. Data visualization and some simple yet powerful statistics for data exploration purposes 6. 6. Dimensionality reduction and feature evaluation 7. 7. Machine learning methods, ranging from unsupervised (different types of clustering) to supervised ones (decision trees, random forests, basic neural networks, regression trees, and Extreme Learning Machines) 8. 8. Graph analysis including pinpointing the connections among the various entities and how they can be mined for useful insights. Each chapter concludes with a series of questions and exercises to reinforce what you learned. The last chapter of the book will guide you in creating a data science application from scratch using Julia.

Getting Started With Julia

Author: Ivo Balbaert
Publisher: Packt Publishing Ltd
ISBN: 1783284803
Size: 37.90 MB
Format: PDF, ePub, Mobi
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This book is for you if you are a data scientist or working on any technical or scientific computation projects. The book assumes you have a basic working knowledge of high-level dynamic languages such as MATLAB, R, Python, or Ruby.

Principles And Theory For Data Mining And Machine Learning

Author: Bertrand Clarke
Publisher: Springer Science & Business Media
ISBN: 0387981357
Size: 77.44 MB
Format: PDF, ePub, Mobi
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Extensive treatment of the most up-to-date topics Provides the theory and concepts behind popular and emerging methods Range of topics drawn from Statistics, Computer Science, and Electrical Engineering

Lightweight Django

Author: Julia Elman
Publisher: "O'Reilly Media, Inc."
ISBN: 149194630X
Size: 42.53 MB
Format: PDF, Kindle
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How can you take advantage of the Django framework to integrate complex client-side interactions and real-time features into your web applications? Through a series of rapid application development projects, this hands-on book shows experienced Django developers how to include REST APIs, WebSockets, and client-side MVC frameworks such as Backbone.js into new or existing projects. Learn how to make the most of Django’s decoupled design by choosing the components you need to build the lightweight applications you want. Once you finish this book, you’ll know how to build single-page applications that respond to interactions in real time. If you’re familiar with Python and JavaScript, you’re good to go. Learn a lightweight approach for starting a new Django project Break reusable applications into smaller services that communicate with one another Create a static, rapid prototyping site as a scaffold for websites and applications Build a REST API with django-rest-framework Learn how to use Django with the Backbone.js MVC framework Create a single-page web application on top of your REST API Integrate real-time features with WebSockets and the Tornado networking library Use the book’s code-driven examples in your own projects

Rapid Prototyping With Js

Author: Azat Mardan
Publisher: Azat Mardan
ISBN:
Size: 54.25 MB
Format: PDF, Kindle
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Rapid Prototyping with JS: Agile JavaScript Development is a hands-on book which introduces you to agile JavaScript web and mobile software development using the latest cutting-edge front-end and back-end technologies including: Node.js, Backbone.js, MongoDB and others. More information at http://rpjs.co. This book was borne out of frustration. I have been in software engineering for many years, and when I started learning Node.js and Backbone.js, I learned the hard way that their official documentation and the Internet lack in quick start guides and examples. Needless to say, it was virtually impossible to find all of the tutorials for JS-related modern technologies in one place. The best way to learn is to do, right? Therefore, I've used the approach of small simple examples, i.e., quick start guides, to expose myself to the new cool tech. After I was done with the basic apps, I needed some references and organization. I started to write this manual mostly for myself, so I can understand the concepts better and refer to the samples later. Then StartupMonthly and I taught a few 2-day intensive classes on the same subject -- helping experienced developers to jump-start their careers with agile JavaScript development. The manual we used was updated and iterated many times based on the feedback received. The end result is this book. What to Expect A typical reader of RPJS should expect a collection of quick start guides, tutorials and suggestions (e.g., Git workflow). There is a lot of coding and not much theory. All the theory we cover is directly related to some of the practical aspects, and essential for better understanding of technologies and specific approaches in dealing with them, e.g., JSONP and cross-domain calls. In addition to coding examples, the book covers virtually all setup and deployment step-by-step. You'll learn on the examples of Chat web/mobile applications starting with front-end components. There are a few versions of these applications, but by the end we'll put front-end and back-end together and deploy to the production environment. The Chat application contains all of the necessary components typical for a basic web app, and will give you enough confidence to continue developing on your own, apply for a job/promotion or build a startup! Who This Book is For The book is designed for advanced-beginner and intermediate-level web and mobile developers: somebody who has been (or still is) an expert in other languages like Ruby on Rails, PHP, Perl, Python or/and Java. The type of a developer who wants to learn more about JavaScript and Node.js related techniques for building web and mobile application prototypes fast. Our target user doesn't have time to dig through voluminous (or tiny, at the other extreme) official documentation. The goal of Rapid Prototyping with JS is not to make an expert out of a reader, but to help him/her to start building apps as soon as possible. Rapid Prototyping with JS: Agile JavaScript Development, as you can tell from the name, is about taking your idea to a functional prototype in the form of a web or a mobile application as fast as possible. This thinking adheres to the Lean Startup30 methodology; therefore, this book would be more valuable to startup founders, but big companies' employees might also find it useful, especially if they plan to add new skills to their resumes. What This Book is Not Rapid Prototyping with JS is neither a comprehensive book on several frameworks, libraries or technologies (or just a particular one), nor a reference for all the tips and tricks of web development. Examples similar to ones in this book might be publicly available online. Even more so, if you're not familiar with fundamental programming concepts like loops, if/else statements, arrays, hashes, object and functions, you won't find them in Rapid Prototyping with JS.

Learning Julia

Author: Anshul Joshi
Publisher: Packt Publishing Ltd
ISBN: 1785885367
Size: 34.99 MB
Format: PDF, Kindle
View: 1634
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Learn Julia language for data science and data analytics About This Book Set up Julia's environment and start building simple programs Explore the technical aspects of Julia and its potential when it comes to speed and data processing Write efficient and high-quality code in Julia Who This Book Is For This book allows existing programmers, statisticians and data scientists to learn the Julia and take its advantage while building applications with complex numerical and scientific computations. Basic knowledge of mathematics is needed to understand the various methods that will be used or created in the book to exploit the capabilities for which Julia is made. What You Will Learn Understand Julia's ecosystem and create simple programs Master the type system and create your own types in Julia Understand Julia's type system, annotations, and conversions Define functions and understand meta-programming and multiple dispatch Create graphics and data visualizations using Julia Build programs capable of networking and parallel computation Develop real-world applications and use connections for RDBMS and NoSQL Learn to interact with other programming languages–C and Python—using Julia In Detail Julia is a highly appropriate language for scientific computing, but it comes with all the required capabilities of a general-purpose language. It allows us to achieve C/Fortran-like performance while maintaining the concise syntax of a scripting language such as Python. It is perfect for building high-performance and concurrent applications. From the basics of its syntax to learning built-in object types, this book covers it all. This book shows you how to write effective functions, reduce code redundancies, and improve code reuse. It will be helpful for new programmers who are starting out with Julia to explore its wide and ever-growing package ecosystem and also for experienced developers/statisticians/data scientists who want to add Julia to their skill-set. The book presents the fundamentals of programming in Julia and in-depth informative examples, using a step-by-step approach. You will be taken through concepts and examples such as doing simple mathematical operations, creating loops, metaprogramming, functions, collections, multiple dispatch, and so on. By the end of the book, you will be able to apply your skills in Julia to create and explore applications of any domain. Style and approach This book demonstrates the basics of Julia along with some data structures and testing tools that will give you enough material to get started with the language from an application standpoint.