How to Install ML Workspace on macOS

Overview

In this tutorial, we will guide you on how to install ML Workspace on your macOS.

Prerequisites

Before we begin with the installation process, make sure you have the following prerequisites:

• macOS 10.12 or later
• Docker Desktop installed on your system

Step 1: Install Docker Desktop

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.

Step 2: Clone ML Workspace Repository

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.

Step 3: Build ML Workspace Docker Image

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.

Step 4: Run ML Workspace

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.