[Bite] Version Control for Data Scientists

May 05, 2022 DataCafé Season 2 Episode 3
[Bite] Version Control for Data Scientists
Show Notes

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 backups
  • recording versions
  • tracking changes
  • experimenting and testing
  • and working with agility.

In this bite episode of the DataCafé we talk about these motivators for version control and how it can strengthen your code development and teamwork in building a data science model, pipeline or product.

Further reading:

Recording date: 21 April 2022

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