Data Science Process
The evolution of the data science process is highlighted, showcasing the five essential stages: obtain, scrub, explore, model, and interpret. It emphasizes the importance of a shared language within the diverse data community, which has grown significantly since 2010. The conversation reflects on how these stages have become foundational for practitioners, while also acknowledging the ongoing challenges faced in the field.In this clip
From this podcast
Super Data Science: ML & AI Podcast with Jon Krohn
SDS 589: Narrative A.I. — with Hilary Mason
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