Doing Data Science: Straight Talk from the Frontline

Based on Schutt's Columbia University course and O'Neil's experience as a data scientist at various startups, this book captures the discipline of data science at the moment it was coalescing from statistics, machine learning, and domain expertise into something with its own identity. Each chapter addresses a practical topic — exploratory data analysis, regression, classification, recommendation engines, MapReduce — but what distinguishes the book is its honesty about the human and organisational dimensions: what gets lost in the pipeline, how models encode assumptions, why communication with non-technical stakeholders matters as much as the algorithm. O'Neil, who would later write Weapons of Math Destruction, already shows her concern with the ethical implications of modelling decisions. The book reads less like a textbook and more like an oral history of a discipline being invented, told by practitioners who are candid about what they do not yet understand.