Przemysław Szufel – författare

Discover the new features and widely used packages in Julia to solve complex computational problems in your statistical applications.Key FeaturesAddress the core problems of programming in Julia with the most popular packages for common tasksTackle issues while working with Databases and Parallel data processing with JuliaExplore advanced features such as metaprogramming, functional programming, and user defined typesBook DescriptionJulia, with its dynamic nature and high-performance, provides comparatively minimal time for the development of computational models with easy-to-maintain computational code. This book will be your solution-based guide as it will take you through different programming aspects with Julia.Starting with the new features of Julia 1.0, each recipe addresses a specific problem, providing a solution and explaining how it works. You will work with the powerful Julia tools and data structures along with the most popular Julia packages. You will learn to create vectors, handle variables, and work with functions. You will be introduced to various recipes for numerical computing, distributed computing, and achieving high performance. You will see how to optimize data science programs with parallel computing and memory allocation. We will look into more advanced concepts such as metaprogramming and functional programming. Finally, you will learn how to tackle issues while working with databases and data processing, and will learn about on data science problems, data modeling, data analysis, data manipulation, parallel processing, and cloud computing with Julia.By the end of the book, you will have acquired the skills to work more effectively with your dataWhat you will learnBoost your code's performance using Julia's unique featuresOrganize data in to fundamental types of collections: arrays and dictionariesOrganize data science processes within Julia and solve related problemsScale Julia computations with cloud computingWrite data to IO streams with Julia and handle web transferDefine your own immutable and mutable typesSpeed up the development process using metaprogrammingWho this book is forThe target audience of this book is data scientists or programmers that want to improve their skills in working with the Julia programming language. It is recommended that the user has a little experience with Julia or intermediate-level experience with other programming languages such as Python, R, or MATLAB.

This book constitutes the proceedings of the 17th International Workshop on Algorithms and Models for the Web Graph, WAW 2020, held in Warsaw, Poland, in September 2020.