Hands-On Julia Programming : An Authoritative Guide to the Production-Ready Systems in Julia (True PDF)
English | 2021 | ISBN: 9391030882 | 338 pages | True PDF | 28 MB
Build production-ready machine learning and NLP systems using functional programming, development platforms, and cloud deployment.
● In-depth explanation and code samples highlighting the features of the Julia language.
● Extensive coverage of the Julia development ecosystem, package management, DevOps environment integration, and performance management tools.
● Exposure to the most important Julia packages that aid in Data and Text Analytics and Deep Learning.
The Julia Programming language enables data scientists and programmers to create prototypes without sacrificing performance. Nonetheless, skeptics question its readiness for production deployments as a new platform with a 1.0 release in 2018. This book removes these doubts and offers a comprehensive glimpse at the language's use throughout developing and deploying production-ready applications.
The first part of the book teaches experienced programmers and scientists about the Julia language features in great detail. The second part consists of gaining hands-on experience with the development environment, debugging, programming guidelines, package management, and cloud deployment strategies. In the final section, readers are introduced to a variety of third-party packages available in the Julia ecosystem for Data Processing, Text Analytics, and developing Deep Learning models.
This book provides an extensive overview of the programming language and broadens understanding of the Julia ecosystem. As a result, it assists programmers, scientists, and information architects in selecting Julia for their next production deployments.
What you will learn
● Get to know the complete fundamentals of Julia programming.
● Explore Julia development frameworks and how to work with them.
● Dig deeper into the concepts and applications of functional programming.
● Uncover the Julia infrastructure for development, testing, and deployment.
● Learn to practice Julia libraries and the Julia package ecosystem.
● Processing Data, Deep Learning, and Natural Language Processing with Julia.