abtest-mlops
This is a continuation of the project started in the Ad campaign performance repository. It sets up a proper MLOps pipeline, holds the ML AB test, and proper Docker deploy configuration.
Data Version Control** or DVC is an open-source tool for data science and machine learning projects. It allows for different versioning and management of datasets and Machine Learning models.
Using github actions we can actually generate ML results for every Pull request and have the info we need right there,
DVC Command Cheat Sheet
git init
dvc init
git commit -m "initial commit"
set dvc remote
dvc remote add -d myremote gdrive://0AIac4JZqHhKmUk9PDA/dvcstore
git commit -m "sets dvc remote"
process which repeats after any modification of data(new version)
adds file to dvc and .gitignore
dvc add path_to_data
git add .gitignore && path_to_data.dvc
git commit -m "data:track"
tags data version on git
git tag -a 'v1' -m "raw data"
dvc push
go ahead and delete the data!
it might also appear in .dvc/cache
to get data back => dvc pull
