Media praise for Doing Data Science

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"I got a lot out of Doing Data Science, finding the chapter organization on business problem specification, analytics formulation, data access/wrangling, and computer code to be very helpful in understanding DS solutions."
-- Steve Miller, Information Management, Co-founder of a Chicago-based business intelligence (BI) services firm OpenBI, LLC

"I enjoyed Rachel and Cathy's book, it's readable, informative, and like no other book I've read on the topic of statistics or data science... It got me thinking about all sorts of things."
-- Andrew Gelman, Statistical Modeling, Causal Inference, and Social Science, Professor of statistics and political science and director of the Applied Statistics Center at Columbia University

"This is a good book to read if you are curious about data science. " Full Review >
-- Mary Anne Thygesen,

"Learn useful techniques and get a feel for what it means to be a "data scientist". " Full Review >
-- Brian Drye,

"Doing Data Science is about the practice of data science, not its implementation. I suspect the students at who were taught using this learned how to find other sources to help them figure things out. But it provides wisdom, which is harder to find and worth quite a bit." Full Review >
-- Kiatikun Luangkesorn,

"The best thing about this book is that in one single investment you get a comprehensive coverage for life on what approach or algorithm to use against a given data science task at hand. You must feel more secure after reading this book and as a result be more eager and ready to embark on any data science project." Full Review >
-- Arthur Zubarev,

"What is data science? The book Doing Data Science not only explains what data science is but also provides a broad overview of methods and techniques that one must master in order to call one self a data scientist." Full Review >
-- Carsten Jorgensen,

"This seemingly intimidating book by Rachel Schutt and Cathy O'Neil is actually quite enjoyable from the very start. Although some of the examples later in the book require a background in statistical mathematics, there is a large section in the beginning of the book dedicated to the history and current state of data science." Full Review >
-- Burke Ingraffia,