{"product_id":"julia-quick-syntax-reference-a-pocket-guide-for-data-science-programming-9798868809644","title":"Julia Quick Syntax Reference: A Pocket Guide for Data Science Programming","description":"\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\u003cbr\u003e\u003cbr\u003e\u003cb\u003eBinding Type:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Apress\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 01\/04\/2025\u003cbr\u003e\u003cb\u003eISBN:\u003c\/b\u003e 9798868809644\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 361\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 1.18lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 9.21h x 6.14w x 0.79d","brand":"Antonello Lobianco","offers":[{"title":"Default Title","offer_id":45419190583477,"sku":"9798868809644","price":46.74,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0473\/0804\/6492\/files\/img_c6c0a185-bd36-4608-afea-f326eddfa9c6.jpg?v=1748391200","url":"https:\/\/pastforward.org\/products\/julia-quick-syntax-reference-a-pocket-guide-for-data-science-programming-9798868809644","provider":"Past Forward","version":"1.0","type":"link"}