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Git for data scientists - manage your code and data together

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Data Science Version Control or DVC is an open source tool for data science projects. It helps data scientists manage their code and data together in a simple form of Git-like commands.

Get started

Step

Command

Track code and data together

$ git add train.py
$ dvc add images.zip

Connect code and data by commands

$ dvc run -d images.zip -o images/ unzip -q images.zip
$ dvc run -d images/ -d train.py -o model.p python train.py

Make changes and reproduce

$ vi train.py
$ dvc repro model.p.dvc

Share code

$ git add .
$ git commit -m 'The baseline model'
$ git push

Share data and ML models

$ dvc remote add myremote s3://mybucket/image_cnn
$ dvc core.remote myremote
$ dvc push

Follow this link to learn more and get more details: get started.

Installation

It could be installed using pip, Homebrew or an OS-specific package.

pip install dvc

Package

Self-contained packages for Windows, Linux, Mac are available. The latest version of the packages can be found at GitHub releases page.

Homebrew

brew install iterative/homebrew-dvc/dvc

or:

brew cask install iterative/homebrew-dvc/dvc

How DVC works

how_dvc_works

Contributing

Contributions are welcome! Please see our Contributing Guide for more details.

Project details


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