Who This Book Is For

This book is for data scientists and data analysts who are familiar with the basics of the Julia language. Prior experience of working with high-level languages such as MATLAB, Python, R, or Ruby is expected.

What You Will Learn

In Detail

Want to handle everything that Julia can throw at you and get the most of it every day? This practical guide to programming with Julia for performing numerical computation will make you more productive and able work with data more efficiently. The book starts with the main features of Julia to help you quickly refresh your knowledge of functions, modules, and arrays. We'll also show you how to utilize the Julia language to identify, retrieve, and transform data sets so you can perform data analysis and data manipulation.

Later on, you'll see how to optimize data science programs with parallel computing and memory allocation. You'll get familiar with the concepts of package development and networking to solve numerical problems using the Julia platform.

This book includes recipes on identifying and classifying data science problems, data modelling, data analysis, data manipulation, meta-programming, multidimensional arrays, and parallel computing. By the end of the book, you will acquire the skills to work more effectively with your data.

Style and approach

This book has a recipe-based approach to help you grasp the concepts of Julia programming.