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Another open-source one that has popped up is DVC

https://github.com/iterative/dvc

Data Science Version Control or DVC is an open-source tool for data science and machine learning projects. With a simple and flexible Git-like architecture and interface

 

DVC is compatible with Git for storing code and the dependency graph (DAG), but not data files cache. To store and share data files cache DVC supports remotes - any cloud (S3, Azure, Google Cloud, etc) or any on-premise network storage (via SSH, for example).

enter image description here

Another open-source one that has popped up is DVC

https://github.com/iterative/dvc

Data Science Version Control or DVC is an open-source tool for data science and machine learning projects. With a simple and flexible Git-like architecture and interface

 

DVC is compatible with Git for storing code and the dependency graph (DAG), but not data files cache. To store and share data files cache DVC supports remotes - any cloud (S3, Azure, Google Cloud, etc) or any on-premise network storage (via SSH, for example).

enter image description here

Another open-source one that has popped up is DVC

https://github.com/iterative/dvc

Data Science Version Control or DVC is an open-source tool for data science and machine learning projects. With a simple and flexible Git-like architecture and interface

DVC is compatible with Git for storing code and the dependency graph (DAG), but not data files cache. To store and share data files cache DVC supports remotes - any cloud (S3, Azure, Google Cloud, etc) or any on-premise network storage (via SSH, for example).

enter image description here

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Another open-source one that has popped up is DVC

https://github.com/iterative/dvc

Data Science Version Control or DVC is an open-source tool for data science and machine learning projects. With a simple and flexible Git-like architecture and interface

DVC is compatible with Git for storing code and the dependency graph (DAG), but not data files cache. To store and share data files cache DVC supports remotes - any cloud (S3, Azure, Google Cloud, etc) or any on-premise network storage (via SSH, for example).

enter image description here