Data Science

In Kyle’s notes, data science is framed through Robert Pottroff’s 2018 tutorial-style walkthrough of the ML landscape. Pottroff distinguishes machine learning (which he ties to a PhD in computer science) from data science (which he ties to a PhD in statistics), treating them as two branches of a common “data science tree.” The framing situates deep learning — function approximation over examples, accelerated by purpose-built hardware — as a sub-branch within that broader family rather than a separate discipline.

Context: Data science is the interdisciplinary practice of extracting insight from data, drawing on statistics, computing, and domain expertise; it overlaps with but is conventionally distinguished from machine learning, which focuses on building predictive models.

Where this appears

• Robert Pottroff — distinguishes ML (CS) from data science (statistics) as branches of one “data science tree.”

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