In this tutorial, we will guide you on how to install ML Workspace on your macOS.
Before we begin with the installation process, make sure you have the following prerequisites:
Navigate to the Docker Desktop website and download the installer for macOS. Once downloaded, run the installer and follow the instructions to install Docker Desktop on your system.
Once Docker Desktop is installed, open the terminal on your macOS and clone the ML Workspace repository by executing the following command:
git clone https://github.com/ml-tooling/ml-workspace.git
This will create a folder named ml-workspace in your current directory.
In your terminal, navigate to the ml-workspace directory and execute the following command to build the Docker image:
docker build --no-cache -t mltooling/ml-workspace .
Note: This may take a few minutes to complete depending on your internet speed.
After the Docker image is built, you can start the ML Workspace by executing the following command:
docker run -p 8080:8080 -v /var/run/docker.sock:/var/run/docker.sock -v "$(pwd):/workspace/data" mltooling/ml-workspace start
This command will start the ML Workspace and you can access it at http://localhost:8080 in your web browser.
Congratulations! You have successfully installed ML Workspace on your macOS. Feel free to explore and use the ML Workspace environment for your machine learning projects.
If you want to self-host in an easy, hands free way, need an external IP address, or simply want your data in your own hands, give IPv6.rs a try!
Alternatively, for the best virtual desktop, try Shells!
