GitHub / JesperDramsch / ml-for-science-reproducibility-tutorial

Increase citations, ease review & collaboration A collection of "easy wins" to make machine learning in research reproducible. This tutorial focuses on basics that work. Getting you 90% of the way to top-tier reproducibility.

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JesperDramsch%2Fml-for-science-reproducibility-tutorial

Commit Stats

Commits: 61
Authors: 2
Mean commits per author: 30.5
Development Distribution Score: 0.033
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/JesperDramsch/ml-for-science-reproducibility-tutorial

Topics: jupyter-book, machine-learning, ml4science, python, reproducibility, science, software-sustainability

Files

Dependencies