[size=11.000000pt]In this book, we want to both describe and prescribe. We want to[size=11.000000pt]describe [size=11.000000pt]the current state of data science by observing a set of top-notchthinkers describe their jobs and what it’s like to “do data science.” Wealso want to [size=11.000000pt]prescribe [size=11.000000pt]what data science could be as an academicdiscipline.
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[size=11.000000pt]Don’t expect a machine learning textbook. Instead, expect full im[size=11.000000pt]‐[size=11.000000pt]mersion into the multifaceted aspects of data science from multiplepoints of view. This is a survey of the existing landscape of datascience—an attempt to map this emerging field—and as a result, thereis more breadth in some cases than depth.
[size=11.000000pt]This book is written with the hope that it will find itself into the handsof someone—you?—who will make even more of it than what it is,and go on to solve important problems.
After the class was over, I heard it characterized as a holistic, humanistapproach to data science—we did not just focus on the tools, math,models, algorithms, and code, but on the human side as well. I likethis definition of humanist: “a person having a strong interest in orconcern for human welfare, values, and dignity.” Being humanist inthe context of data science means recognizing the role your ownhumanity plays in building models and algorithms, thinking aboutqualities you have as a human that a computer does not have (whichincludes the ability to make ethical decisions), and thinking about thehumans whose lives you are impacting when you unleash a model ontothe world.
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