15 min

[Bite] Version Control for Data Scientists DataCafé

    • Science

Data scientists usually have to write code to prototype software, be it to preprocess and clean data, engineer features, build a model, or deploy a codebase into a production environment or other use case. The evolution of a codebase is important for a number of reasons which is where version control can help, such as:collaborating with other code developers (due diligence in coordination and delegation)generating backupsrecording versionstracking changesexperimenting and testingand working w...

Data scientists usually have to write code to prototype software, be it to preprocess and clean data, engineer features, build a model, or deploy a codebase into a production environment or other use case. The evolution of a codebase is important for a number of reasons which is where version control can help, such as:collaborating with other code developers (due diligence in coordination and delegation)generating backupsrecording versionstracking changesexperimenting and testingand working w...

15 min

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