Testing in Data Science
Data scientists can greatly benefit from adopting engineering practices, particularly in testing methodologies. While traditional unit testing is prevalent in software development, it remains underutilized in data science, where mock data can be employed to validate algorithms. Emphasizing the importance of documentation and testing can enhance collaboration between data scientists and engineers, ultimately leading to more robust models.In this clip
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Software Engineering Radio - the podcast for professional software developers
SE-Radio Episode 315: Jeroen Janssens on Tools for Data Science
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