In this tutorial, we will guide you on how to install the ML Workspace on MXLinux Latest operating system. ML Workspace is an open-source web-based platform for Machine Learning and Data Science that provides a simple user interface to manage data, code, models, and multiple instances of Jupyter notebooks.
Before we proceed with the installation, make sure you have the following prerequisites:
Before starting the installation process, it is always recommended to update your system to the latest version.
sudo apt-get update && sudo apt-get upgrade
This command will update the package manager and upgrade any installed packages.
The next step is to install Docker on your MXLinux Latest operating system. You can use the following command to install Docker.
sudo apt-get install docker.io
Once the installation is complete, start the Docker service.
sudo systemctl start docker.service
Check the status of the Docker service using the following command.
sudo systemctl status docker.service
Now we are ready to install the ML Workspace. To install the ML Workspace, we will use Docker Compose.
Start by creating a new directory to store the Docker Compose file.
mkdir ml-workspace && cd ml-workspace
Next, create a new Docker Compose file named "docker-compose.yaml".
nano docker-compose.yml
Paste the following code into the newly created file.
version: '3'
services:
ml-workspace:
image: mltooling/ml-workspace:latest
ports:
- "8080:8080"
environment:
- STARTUP_CMD=python3 mlwb/server/main.py
- WORKSPACE_ENABLE_GPU=true
- WORKSPACE_UID=1000
- WORKSPACE_GID=1000
- WORKSPACE_BASE_URL=ml-workspace
volumes:
- workspace-folder:/workspace
- /var/run/docker.sock:/var/run/docker.sock
volumes:
workspace-folder:
This Docker Compose file defines a service named "ml-workspace" that uses the latest ML Workspace Docker image. It maps port 8080 of the container to port 8080 of the host machine. It also sets some environment variables to enable GPU usage, set user and group IDs, and define the base URL. It also mounts the workspace folder and the Docker socket to the container.
Now, start the ML Workspace using Docker Compose.
sudo docker-compose up -d
The "-d" option runs the Docker Compose in the background. This process may take 5-10 minutes, depending on your internet connection speed.
Once the installation process is complete, you can check the status of the running containers using the following command.
docker-compose ps
This command should display the status of the "ml-workspace" service. If it is up and running, you can access the ML Workspace by opening a web browser and navigating to "http://localhost:8080".
The first time you access the ML Workspace, you will be asked to create a new user account. Provide your email address and password to sign up. Once you have signed up, you will be directed to the dashboard, where you can create and manage your workspace.
Congratulations! You have successfully installed the ML Workspace on your MXLinux Latest operating system. Now you can easily perform machine learning and data science tasks using the web-based interface.
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