Julia 1.0 Programming Complete Reference Guide: discover Julia, a high-performance language for technical computing
bLearn dynamic programming with Julia to build apps for data analysis, visualization, machine learning, and the web/b h4Key Features/h4 ul liLeverage Julia's high speed and efficiency to build fast, efficient applications /li liPerform supervised and unsupervised machine learning and time serie...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham ; Mumbai
Packt
May 2019
|
| Ausgabe: | 1 |
| Schlagworte: | |
| Online-Zugang: | UBY01 |
| Zusammenfassung: | bLearn dynamic programming with Julia to build apps for data analysis, visualization, machine learning, and the web/b h4Key Features/h4 ul liLeverage Julia's high speed and efficiency to build fast, efficient applications /li liPerform supervised and unsupervised machine learning and time series analysis /li liTackle problems concurrently and in a distributed environment /li /ul h4Book Description/h4 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: ul liJulia 1.0 Programming - Second Edition by Ivo Balbaert/li liJulia Programming Projects by Adrian Salceanu/li /ul h4What you will learn/h4 ul liCreate your own types to extend the built-in type system /li liVisualize your data in Julia with plotting packages /li liExplore the use of built-in macros for testing and debugging /li liIntegrate Julia with other languages such as C, Python, and MATLAB /li liAnalyze and manipulate datasets using Julia and DataFrames /li liDevelop and run a web app using Julia and the HTTP package /li liBuild a recommendation system using supervised machine learning/li/ul h4Who this book is for/h4 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 |
| Beschreibung: | 1 Online-Ressource (viii, 440 Seiten) |
| ISBN: | 9781838824679 |
Internformat
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| 520 | |a bLearn dynamic programming with Julia to build apps for data analysis, visualization, machine learning, and the web/b h4Key Features/h4 ul liLeverage Julia's high speed and efficiency to build fast, efficient applications /li liPerform supervised and unsupervised machine learning and time series analysis /li liTackle problems concurrently and in a distributed environment /li /ul h4Book Description/h4 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. | ||
| 520 | |a 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. | ||
| 520 | |a This Learning Path includes content from the following Packt products: ul liJulia 1.0 Programming - Second Edition by Ivo Balbaert/li liJulia Programming Projects by Adrian Salceanu/li /ul h4What you will learn/h4 ul liCreate your own types to extend the built-in type system /li liVisualize your data in Julia with plotting packages /li liExplore the use of built-in macros for testing and debugging /li liIntegrate Julia with other languages such as C, Python, and MATLAB /li liAnalyze and manipulate datasets using Julia and DataFrames /li liDevelop and run a web app using Julia and the HTTP package /li liBuild a recommendation system using supervised machine learning/li/ul h4Who this book is for/h4 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 | ||
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| format | Electronic eBook |
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| spelling | Balbaert, Ivo Verfasser (DE-588)1036706737 aut Julia 1.0 Programming Complete Reference Guide discover Julia, a high-performance language for technical computing Ivo Balbaert, Adrian Salceanu 1 Birmingham ; Mumbai Packt May 2019 1 Online-Ressource (viii, 440 Seiten) txt rdacontent c rdamedia cr rdacarrier bLearn dynamic programming with Julia to build apps for data analysis, visualization, machine learning, and the web/b h4Key Features/h4 ul liLeverage Julia's high speed and efficiency to build fast, efficient applications /li liPerform supervised and unsupervised machine learning and time series analysis /li liTackle problems concurrently and in a distributed environment /li /ul h4Book Description/h4 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: ul liJulia 1.0 Programming - Second Edition by Ivo Balbaert/li liJulia Programming Projects by Adrian Salceanu/li /ul h4What you will learn/h4 ul liCreate your own types to extend the built-in type system /li liVisualize your data in Julia with plotting packages /li liExplore the use of built-in macros for testing and debugging /li liIntegrate Julia with other languages such as C, Python, and MATLAB /li liAnalyze and manipulate datasets using Julia and DataFrames /li liDevelop and run a web app using Julia and the HTTP package /li liBuild a recommendation system using supervised machine learning/li/ul h4Who this book is for/h4 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 COMPUTERS / Programming Languages / Python COMPUTERS / Internet / Application Development Salceanu, Adrian Sonstige (DE-588)1179294580 oth Erscheint auch als Druck-Ausgabe 978-1-83882-224-8 |
| spellingShingle | Balbaert, Ivo Julia 1.0 Programming Complete Reference Guide discover Julia, a high-performance language for technical computing COMPUTERS / Programming Languages / Python COMPUTERS / Internet / Application Development |
| title | Julia 1.0 Programming Complete Reference Guide discover Julia, a high-performance language for technical computing |
| title_auth | Julia 1.0 Programming Complete Reference Guide discover Julia, a high-performance language for technical computing |
| title_exact_search | Julia 1.0 Programming Complete Reference Guide discover Julia, a high-performance language for technical computing |
| title_exact_search_txtP | Julia 1.0 Programming Complete Reference Guide discover Julia, a high-performance language for technical computing |
| title_full | Julia 1.0 Programming Complete Reference Guide discover Julia, a high-performance language for technical computing Ivo Balbaert, Adrian Salceanu |
| title_fullStr | Julia 1.0 Programming Complete Reference Guide discover Julia, a high-performance language for technical computing Ivo Balbaert, Adrian Salceanu |
| title_full_unstemmed | Julia 1.0 Programming Complete Reference Guide discover Julia, a high-performance language for technical computing Ivo Balbaert, Adrian Salceanu |
| title_short | Julia 1.0 Programming Complete Reference Guide |
| title_sort | julia 1 0 programming complete reference guide discover julia a high performance language for technical computing |
| title_sub | discover Julia, a high-performance language for technical computing |
| topic | COMPUTERS / Programming Languages / Python COMPUTERS / Internet / Application Development |
| topic_facet | COMPUTERS / Programming Languages / Python COMPUTERS / Internet / Application Development |
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