In this tutorial, we will walk you through the steps to install ML Workspace on Ubuntu Server Latest. ML Workspace is an all-in-one web-based IDE for machine learning and data science. It comes pre-installed with various popular machine learning libraries and frameworks, making it a great tool for beginners and advanced users alike.
Before we start with the installation, you must ensure that the following prerequisites are met:
Here are the steps to install ML Workspace on Ubuntu Server Latest:
The first step is to ensure that your server is up-to-date with the latest packages. You can do this by running the following commands in the terminal:
sudo apt update
sudo apt upgrade
ML Workspace is packaged as a Docker container, so you will need to install Docker on your server. You can do this by running the following commands:
sudo apt install docker.io
sudo systemctl enable --now docker
sudo usermod -aG docker your-user
After running the above commands, log out and log in to your server to apply the group changes.
Next, you will need to install Docker-Compose. Docker-Compose is a tool that allows you to define and run multi-container Docker applications.
You can install Docker-Compose by running the following commands:
sudo curl -L "https://github.com/docker/compose/releases/download/1.29.2/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
sudo chmod +x /usr/local/bin/docker-compose
After installing Docker-Compose, verify the installation by running the following command:
docker-compose --version
Next, you will need to clone the ML Workspace repository. You can do this by running the following command:
git clone https://github.com/ml-tooling/ml-workspace.git
After cloning the repository, navigate to the ml-workspace directory and open the .env file. This file contains the configuration for the ML Workspace environment.
You can configure the environment based on your preferences. By default, ML Workspace comes with pre-installed machine learning libraries and frameworks.
After configuring the environment, you can build and launch the ML Workspace container. You can do this by running the following commands:
cd ml-workspace
sudo docker-compose up -d --build
After launching the container, you can access the ML Workspace web interface by opening your web browser and navigating to the IP address or domain name of your server. The default port is 8080.
http://{SERVER_IP}:8080
When you open the ML Workspace web interface for the first time, you will be asked to create a user account. After creating the account, you will be redirected to the workspace dashboard.
Congratulations! You've successfully installed ML Workspace on your Ubuntu Server Latest.
In this tutorial, we've shown you how to install ML Workspace on Ubuntu Server Latest. ML Workspace is an all-in-one web-based IDE for machine learning and data science. It comes pre-installed with various popular machine learning libraries and frameworks, making it a great tool for beginners and advanced users alike.
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