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Data Science Stack ✨

Making it seamless to run GPU enabled containerized ML Environments

Overview

The Data Science Stack (DSS) makes it seamless for everyone to jump into an ML Environment within minutes and be able to utilise their GPUs.

DSS is a ready-made environment which allows everyone to run ML workloads on the laptop. It gives easy access to a solution for developing and optimising ML models, that leverages the GPUs of the laptop by enabling users to utilise different ML environment images based on their needs.

The DSS is a stack that includes

  • a container orchestration system (microK8s snap)
  • out-of-the box containerized ML Environments
  • an intuitive CLI which streamlines the management of those containers (data-science-stack snap)

The container orchestration system also handles the integration with the host's GPU and drivers, so the containerized environments can only focus on user-space libraries.

Features

  • Containerized environment management
  • Seamless GPU utilization
  • Out-of-the box ML Environments with JupyterLab
  • Easy data passing between local machine and containerized ML Environments
  • MLflow for lineage tracking

Requirements

  • Ubuntu 22.04
  • Snapcraft (included in Ubuntu)

Quick Start

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Resources

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Feedback

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