In this tutorial, we'll compare ML models across two different Git branches of a project- and we'll do it in a continuous integration system (GitHub Actions) for automation superpowers! We'll cover:
Why comparing model metrics takes more than a git diff
How pipelines, a method for making model training more reproducible, help you standardize model comparisons across Git branches
How to display a table comparing model performance to the main branch in a GitHub Pull Request
** Need an intro to GitHub Actions and continuous integration? Check out the first video in this series! • MLOps Tutorial #1: Intro to Continuous Int... **
Helpful links:
Dataset: https://www.sciencedirect.com/science...
Code: https://github.com/elleobrien/farmer
DVC pipelines & metrics documentation: https://dvc.org/doc/start/data-pipeli...
CML project repo: https://github.com/iterative/cml
DVC Discord channel: / discord
🧑🏽💻 To learn more. about our tools, take our free online course at https://learn.iterative.ai
In questa pagina del sito puoi guardare il video online MLOps Tutorial #3: Track ML models with Git & GitHub Actions della durata di ore minuti seconda in buona qualità , che l'utente ha caricato DVCorg 17 agosto 2020, condividi il link con amici e conoscenti, su youtube questo video è già stato visto 25,252 volte e gli è piaciuto 641 spettatori. Buona visione!