{"product_id":"julia-quick-syntax-reference-a-pocket-guide-for-data-science-programming-paperback","title":"Julia Quick Syntax Reference: A Pocket Guide for Data Science Programming - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eAntonello Lobianco\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eLearn the Julia programming language as quickly as possible. This book is a must-have reference guide that presents the essential Julia syntax in a well-organized format, updated with the latest features of Julia's APIs, libraries, and packages.\u003c\/p\u003e \u003cp\u003eThis 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. At a more applied level, you will learn how to use Julia packages for data analysis, numerical optimization, symbolic computation, and machine learning, and how to present your results in dynamic documents.\u003c\/p\u003e \u003cp\u003eThe Second Edition delves deeper into modules, environments, and parallelism in Julia. It covers random numbers, reproducibility in stochastic computations, and adds a section on probabilistic analysis. Finally, it provides forward-thinking introductions to AI and machine learning workflows using BetaML, including regression, classification, clustering, and more, with practical exercises and solutions for self-learners.\u003c\/p\u003e \u003cp\u003e\u003cstrong\u003eWhat You Will Learn \u003c\/strong\u003e\u003c\/p\u003e \u003cul\u003e \u003cli\u003eWork with Julia types and the different containers for rapid development\u003c\/li\u003e \u003cli\u003eUse vectorized, classical loop-based code, logical operators, and blocks\u003c\/li\u003e \u003cli\u003eExplore Julia functions: arguments, return values, polymorphism, parameters, anonymous functions, and broadcasts\u003c\/li\u003e \u003cli\u003eBuild custom structures in Julia\u003c\/li\u003e \u003cli\u003eUse C\/C++, Python or R libraries in Julia and embed Julia in other code.\u003c\/li\u003e \u003cli\u003eOptimize performance with GPU programming, profiling and more.\u003c\/li\u003e \u003cli\u003eManage, prepare, analyse and visualise your data with DataFrames and Plots\u003c\/li\u003e \u003cli\u003eImplement complete ML workflows with BetaML, from data coding to model evaluation, and more.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003cstrong\u003eWho This Book Is For\u003c\/strong\u003e\u003c\/p\u003e \u003cp\u003eExperienced programmers who are new to Julia, as well as data scientists who want to improve their analysis or try out machine learning algorithms with Julia.\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eAntonello Lobianco, PhD is a research engineer employed by a French Grande É cole (polytechnic university). He works on the biophysical and economic modelling of the forest sector and is responsible for the lab models portfolio. He does programming in C++, Perl, PHP, Visual Basic, Python, and Julia. He teaches environmental and forest economics at undergraduate and graduate levels and modelling at PhD level. For a few years, he has followed the development of Julia as it fits his modelling needs. He is the author of a few Julia packages, particularly on data analysis and machine learning (search sylvaticus on GitHub). \u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 361\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.79 x 9.21 x 6.14 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e January 04, 2025\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":53429837955379,"sku":"9798868809644","price":66.38,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0300\/5595\/6612\/files\/CAFRClN8-P9798868809644.webp?v=1780647014","url":"https:\/\/www.vysn.com\/products\/julia-quick-syntax-reference-a-pocket-guide-for-data-science-programming-paperback","provider":"VYSN","version":"1.0","type":"link"}