This hands-on guide is aimed at practitioners in the area of data science. The book assumes some previous skills with Julia and in coding in a scripting language such as Python, Matlab, or R-or otherwise in a compiled language such as C, Fortran, or Java. Experience in specific study areas such as database, networking, statistics, and mathematics is not required.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Key Features
Book Description
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.
What You Will Learn
About the Author
Malcolm Sherrington has been working in computing for over 35 years. He currently runs his own company in the finance sector, and is particularly interested in High Performance Computing and applications of GPUs and parallelism. Malcolm is also the organizer of the London Julia User Group, and co-organizer of the UK High Performance Computing and the financial engineers and Quant London meetup groups.
Table of Contents
Malcolm Sherrington
Malcolm Sherrington has been working in computing for over 35 years. He holds degrees in mathematics, chemistry, and engineering and has given lectures at two different universities in the UK as well as worked in the aerospace and healthcare industries. Currently, he is running his own company in the finance sector, with specific interests in High Performance Computing and applications of GPUs and parallelism. Always hands-on, Malcolm started programming scientific problems in Fortran and C, progressing through Ada and Common Lisp, and recently became involved with data processing and analytics in Perl, Python, and R. Malcolm is the organizer of the London Julia User Group. In addition, he is a co-organizer of the UK High Performance Computing and the financial engineers and Quant London meetup groups.
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