An introduction to Julia, Gen.jl, and a few other machine-learning libraries.
- Clone (using
git
) or download (via the "Download ZIP" button under "Code") this repository. - Make sure you have Docker installed locally. (However, if you have Julia
1.6, then use the
Project.toml
file here.) - Run the
setup.sh
script by opening a Terminal and running./setup.sh
. - Then you should use that same Terminal to run
docker-compose up
. - Wait a few seconds for JupyterLab to start, then head over to port:
46876
(or this link).
NOTE: watch for OS-specific caveats.
- Follow along Docker's "Getting Started" page until the "Docker Dashboard" heading. (For Windows and MacOS users, I recommend installing Docker Desktop.)
- Ensure that you have Git installed. This guide should walk you through
everything. I recommend using the either pure
git
or the GitHub CLI for GitHub projects (like this one); however, GitHub Desktop is also a perfectly good solution.
- In the past, you needed Windows 10 Pro / Education. I'm not sure if this requirement still stands. You may need to upgrade to these editions if Docker fails to start.
- The Linux installation doesn't provide Docker Compose (a toolchain atop Docker). Follow these steps to install Docker Compose.
- To avoid using
sudo docker <blah>
, add yourself to the docker group using the following command:sudo usermod -aG docker $(whoami)
. - Linux must use
git
(or the GitHub CLI) through the command-line.