Lobianco Antonello. Julia Quick Syntax Reference: A Pocket Guide for Data Science Programming

2nd Edition. — Apress Media LLC, 2025. — 325 p. — ISBN-13 979-8-8688-0964-4.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 PlotsIntroduction
Language Core
Getting Started
Data Types and Structures
Control Flow and Functions
Custom Types
Input/Output
Metaprogramming and Macros
Interfacing Julia with Other Languages
Efficiently Write Efficient Code
Parallel Computing in Julia
Packages Ecosystem
Working with Data
Scientific Libraries
AI with Julia
Utilities
Index