Julia Quick Syntax Reference

A Pocket Guide for Data Science Programming

von Antonello Lobianco

361 Seiten, Taschenbuch

Kurzbeschreibung des Verlags

Learn 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.

This 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.

The 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.

What You Will Learn  

Work with Julia types and the different containers for rapid development

Use vectorized, classical loop-based code, logical operators, and blocks

Explore Julia functions: arguments, return values, polymorphism, parameters, anonymous functions, and broadcasts

Build custom structures in Julia

Use C/C++, Python or R libraries in Julia and embed Julia in other code.

Optimize performance with GPU programming, profiling and more.

Manage, prepare, analyse and visualise your data with DataFrames and Plots

Implement complete ML workflows with BetaML, from data coding to model evaluation, and more.

Who This Book Is For

Experienced 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.

 

• Themen: Informatik und Informationstechnologie Computerprogrammierung und Softwareentwicklung Compiler und Übersetzer
• ISBN: 9798868809644
• Sprache: Englisch
• Erscheinungsdatum: 04.01.2025
• Größe: 23.5 x 15.5 cm
• Verlag: APRESS