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
Files
(467.2 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:18ed4f637feb530586a496313dc2eef8
|
467.2 kB | Preview Download |
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)