Join Barton Poulson for an in-depth discussion in this video What is Julia?, part of Julia for Data Scientists First Look.
- [Narrator] Julia is a language designed for technical computing. There's a few reasons for having a new language here. The goals of Julia are: one, to make it easy, as easy to use and as clear to read as Python; second, is to make it fast and as fast as a statically typed language like C; and then third, to make it capable for technical computing, as good as R or MATLAB for numerical work. Now these are very ambitious goals, and Julia is still in its developmental phase and as it goes through it will continue to work towards these particular goals.
But I wanna add something else. Julia has an advantage of connectability. You can run C, Fortran, R, Python, or even MATLAB code from within Julia, and C runs natively without wrappers or shells. Types: there are over 340 types available in Julia. They are dynamic types, and also you can create your own custom user-defined types. Julia has great macro processing. It allows you to do all sorts of metaprogramming. And then, perhaps on a smaller note, Julia take unicode, so you have an expanded character set, including Greek letters or other symbols that you might need to use for your mathematics.
And then finally, Julia is open source and free. Julia, a new technical language, is designed for ease of use and speed of execution. It's free, it's open source, and it's extensible through many other languages. And Julia makes a compelling choice for work in data science.