ML environments at ease on your AI workstation
Data science stack (DSS) is a ready-to-run environment for machine learning and data science. It’s built on open-source tooling (including MicroK8s, JupyterLab and MLFlow) and is usable on any Ubuntu/Snap-enabled workstation.
DSS provides a CLI for managing containerised ML environment images such as PyTorch or TensorFlow, on top of MicroK8s.
Typically, creating ML environments on a workstation involves complex and hard-to-reverse configuration. DSS solves this problem by making accessible, production-ready, isolated and reproducible ML environments, that make full use of a workstation’s GPUs.
Both ML beginners and engineers who need to build complex development and runtime environments will see set-up time reduced to a minimum, allowing them to get on with useful work within minutes.