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:
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
Thanks for joining us in the DataCafé. You can follow us on twitter @DataCafePodcast and feel free to contact us about anything you've heard here or think would be an interesting topic in the future.
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:
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
Thanks for joining us in the DataCafé. You can follow us on twitter @DataCafePodcast and feel free to contact us about anything you've heard here or think would be an interesting topic in the future.