Julia was designed for high performance. Julia programs automatically compile to efficient native code via LLVM, and support multiple platforms. Julia is dynamically typed, feels like a scripting language, and has good support for interactive use, but can also optionally be separately compiled.
Julia is a high-level, high-performance dynamic language for technical computing. The main homepage for Julia can be found at julialang.org. This is the GitHub repository of Julia source code, including instructions for compiling and installing Julia, below.
Julia is a high-performance open source programming language designed for scientific and numerical computing. Created to solve the "two-language problem," Julia combines the ease and expressiveness of languages like Python and R with performance comparable to C/C++.
Julia is a dynamic, high-performance programming language that is used to perform operations in scientific computing. Similar to R Programming Language, Julia is used for statistical computations and data analysis.
Julia is an open-source project known for its high performance and ability to generate highly efficient code at speeds approaching those of languages like C and Fortran. A dynamic language, Julia is relatively easy for programmers to learn and adapt.
A comprehensive introductory tutorial that will help you master the fundamentals of Julia. Learn about operators, conditional statements, working with DataFrames, and more.
The Julia programming language is easy to use, fast, and powerful. This wikibook is intended as an introduction to the language for the less experienced and occasional programmer.
The definitive source for learning all things Julia. Prepared by core Julia developers in collaboration with Julia Computing. - JuliaAcademy