Published March 24, 2023 | Version v1
Preprint Open

Detailed Implementation of a Reproducible Machine Learning-Enabled Workflow

  • 1. Global Biodata Coalition, 12 quai Saint-Jean 67080, Strasbourg, France and Department of Biosystems Engineering, The University of Arizona, Tucson, Arizona 85721, USA
  • 2. University Library, University of Illinois at Urbana-Champaign, Urbana, Illinois 31821, USA and Global Biodata Coalition, 12 quai Saint-Jean 67080, Strasbourg, France
  • 3. Global Biodata Coalition, 12 quai Saint-Jean 67080, Strasbourg, France

Description

This manuscript is a "comment" article describing the efforts made in developing a reproducible machine learning-enabled workflow. We intend to submit this manuscript for peer review.

Files

detailed_implementation_of_a_reproducible_machine_learning-enabled_workflow.pdf

Additional details

Related works

Describes
Proposal: 10.5281/zenodo.7392518 (DOI)
Workflow: 10.5281/zenodo.7768363 (DOI)
Workflow: 10.17504/protocols.io.5jyl89o36v2w/v3 (DOI)
Is cited by
Preprint: 10.5281/zenodo.7768415 (DOI)
Preprint: 10.5281/zenodo.7974994 (DOI)