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A practical approach for creating machine learning CI/CD Pipeline with DVC that is data version control.

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Sengarofficial/Machine_Learning_With_DVC

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Create environment

'''bash python - m venv venv '''

activate env '''bash venv/Scripts/venv '''

create req file

install the req '''bash pip install -r requirements.txt '''

download the data from

https://www.kaggle.com/datasets/rajyellow46/wine-quality?resource=download

'''bash git init

'''

'''bash dvc init

'''

'''bash dvc add remote_data/winequalityN.csv

'''

'''bash git add .

'''

'''bash git commit -m "First Commit"

'''

""" After running dvc add remote_data/winequalityN.csv, .gitignore file is created once initialized and it is not uploading the csv file instead keeping the version of it md5 checksome format...!!! naming it's size and where it is located now.

"""

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A practical approach for creating machine learning CI/CD Pipeline with DVC that is data version control.

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