This is my first end to end MLOps project on wine quality prediction dataset.
I have created a pipeline involving modular coding on Visual Studio Code, integrated and created workflow actions on Git, tested the API's on Postman & deployed the app on heroku platform.
Heroku app link: https://winequality-dvc.herokuapp.com GitHub link : https://github.com/PrasannaMaddipati/MLOps_dvc_demo
create env
conda create -n wineq python=3.7 -y
activate env
conda activate wineq
created a req file
install the req
pip install -r requirements.txt
download the data from
https://drive.google.com/drive/folders/18zqQiCJVgF7uzXgfbIJ-04zgz1ItNfF5?usp=sharing
git init
dvc init
dvc add data_given/winequality.csv
git add .
git commit -m "first commit"
oneliner updates for readme
git add . && git commit -m "update Readme.md"
git remote add origin https://github.com/PrasannaMaddipati/MLOps_dvc_demo.git
git branch -M main
git push origin main
tox command -
tox
for rebuilding -
tox -r
pytest command
pytest -v
setup commands -
pip install -e .
build your own package commands-
python setup.py sdist bdist_wheel