Julia 1.x By Example

A step-by-step guide that demonstrates how to build simple-to-advanced applications through examples in Julia Lang 1.x using modern tools
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Julia 1.x By Example

Adrian Salceanu

A step-by-step guide that demonstrates how to build simple-to-advanced applications through examples in Julia Lang 1.x using modern tools
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Book Details

ISBN 139781788292740
Paperback378 pages

Book Description

Julia is a young programming language that offers a unique combination of performance and productivity and promises to change scientific and general computing.

Beginning with an introduction to the language and its syntax, the book will go on to illustrate how to analyze and manipulate the Iris dataset using Julia and DataFrames. Then you will explore functions, learn about Julia’s type system, and use methods and multiple dispatches to build a web scraper. Further, you’ll delve into more advanced topics such as supervised machine learning, where you’ll build a recommender system for a dating website. Next you will see how to apply unsupervised machine learning techniques to perform data clustering using the San Francisco businesses database. After a quick detour into metaprogramming, the final chapters will address time series (as well as date and time manipulation), time series visualization, and forecasting. By the end of the book, you will have gained the practical knowledge necessary to build statistical models and real-life projects in Julia.

Table of Contents

What You Will Learn

  • Leverage Julia Lang's features, work with packages, and understand IDE options
  • Analyze and manipulate datasets using Julia and DataFrames
  • Write increasingly complex code while building real-life Julia applications
  • Utilize functions, methods, user-defined types, and various control flows available with Julia; and understand multiple dispatch
  • Develop and run a web app using Julia and the HTTP package
  • Build a recommender system employing supervised machine learning with Julia using available packages
  • Perform exploratory data analysis and clustering and apply unsupervised machine learning algorithms 
  • Learn to perform time series data analysis, visualization, and forecasting

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Table of Contents

Book Details

ISBN 139781788292740
Paperback378 pages
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