Doing Data Science Straight Talk from the Frontline

ISBN-10: 1449358659

ISBN-13: 9781449358655

Edition: 2013

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Now that answering complex and compelling questions with data can make the difference in an election or a business model, data science is an attractive discipline. But how can you learn this wide-ranging, interdisciplinary field? With this book, you’ll get material from Columbia University’s "Introduction to Data Science" class in an easy-to-follow format.Each chapter-long lecture features a guest data scientist from a prominent company such as Google, Microsoft, or eBay teaching new algorithms, methods, or models by sharing case studies and actual code they use. You’ll learn what’s involved in the lives of data scientists and be able to use the techniques they present.Guest lectures focus on topics such as:Machine learning and data mining algorithmsStatistical models and methodsPrediction vs. descriptionExploratory data analysisCommunication and visualizationData processingBig dataProgrammingEthicsAsking good questionsIf you’re familiar with linear algebra, probability and statistics, and have some programming experience, this book will get you started with data science.Doing Data Science is collaboration between course instructor Rachel Schutt (also employed by Google) and data science consultant Cathy O’Neil (former quantitative analyst for D.E. Shaw) who attended and blogged about the course.
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Book details

List price: $35.99
Copyright year: 2013
Publisher: O'Reilly Media, Incorporated
Publication date: 11/3/2013
Binding: Paperback
Pages: 300
Size: 6.00" wide x 9.00" long x 1.00" tall
Weight: 1.430
Language: English

Rachel Schutt is the Senior Vice President for Data Science at News Corp. She earned a PhD in Statistics from Columbia University, and was a statistician at Google Research for several years. She is an adjunct professor in Columbia’s Department of Statistics and a founding member of the Education Committee for the Institute for Data Sciences and Engineering at Columbia. She holds several pending patents based on her work at Google, where she helped build user-facing products by prototyping algorithms and building models to understand user behavior. She has a master's degree in mathematics from NYU, and a master's degree in Engineering-Economic Systems and Operations Research from Stanford University. Her undergraduate degree is in Honors Mathematics from the University of Michigan.

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