Julia is a high-level programming language. It was built with high performance in mind, especially with regard to numerical computing. As such, it is a custom-made language for data science use.
We will now cover the steps to add the Julia engine and execute a Julia script under Jupyter.
I know that in previous instances of Jupyter, Julia was automatically installed as an engine in non-Windows environments. I do not have access to another environment, so we will walk through the steps to installing Julia on Windows.
The first step is to download and install the appropriate version from the Julia downloads page, https://julialang.org/downloads. I noticed that there are installs available for macOS and Linux from this page as well. In my case, I could use the 64-bit self-extracting executable. Once installed, we can start the Julia environment, which has a splash screen like this:
Now that Julia is installed, we can request the...