Julia 1.0 Programming Complete Reference Guide
- 466 stránok
- 17 hodin čítania
Learn dynamic programming with Julia to create applications for data analysis, visualization, machine learning, and the web. This resource leverages Julia's speed and efficiency to build fast applications, perform machine learning, and tackle problems in distributed environments. Julia combines the productivity of Python and R with the speed of C++, making it ideal for various domains like fintech and AI. You will start by setting up a Julia platform and exploring built-in types, focusing on arrays and matrices. The Learning Path covers type conversions, interactions with operating systems, and the use of macros, highlighting Julia's suitability for numerical and scientific computing. You'll also learn to run external programs and analyze the Iris dataset using DataFrames. As you build a web scraper and app, you'll explore functions, methods, and multiple dispatches. The final chapters introduce machine learning concepts, culminating in the creation of a book recommender system. By the end, you'll be proficient in Julia and equipped to utilize its capabilities for your applications. This Learning Path is designed for statisticians and data scientists seeking a quick introduction to Julia while building big data applications. Basic knowledge of programming concepts is recommended.
