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@JesperDramsch JesperDramsch released this 03 Dec 13:45
· 44 commits to main since this release
PyData-Global-2022
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Learn about vigilant mode.

Numerous scientific disciplines have noticed a reproducibility crisis of published results. While this important topic was being addressed, the danger of non-reproducible and unsustainable research artefacts using machine learning in science arose. The brunt of this has been avoided by better education of reviewers who nowadays have the skills to spot insufficient validation practices. However, there is more potential to further ease the review process, improve collaboration and make results and models available to fellow scientists. This workshop will teach practical lessons that can be directly applied to elevate the quality of ML applications in science by scientists.

realworld-ml.xyz

What's Changed

  • PR to Fix environment setup, README and dry-run of all existing notebooks by @leriomaggio in #1
  • Expanded example in Model Evaluation + updated scripts and rendered notebooks by @leriomaggio in #2

New Contributors

Full Changelog: EuroSciPy-2022...PyData-Global-2022

Contributors

leriomaggio
Assets 2
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