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DVC Pipelines

We build upon the introductory DVC demo and add the tracking of ML artefact lineage from data and the underlying ML pipeline source code.

Demo Objectives

  • How to initialise a DVC pipelines project.
  • How to develop a ML pipeline for use with DVC.
  • How to run a ML pipeline via DVC and track the resulting artefacts.
  • How to retrieve pipeline run metrics.

Running the Demo

This demo is contained within a single Jupyter notebook - demos/dvc-pipelines/dvc_pipelines.ipynb. Make sure you have the necessary Python package requirements installed into a Jupyter kernel for it to run successfully.