Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions
ISBN: 1260452778
EAN13: 9781260452778
Language: English
Publication Date: April 19, 2019
Pages: 416
Weight: 1.74 lbs.
Format: Hardcover
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Book Overview
The first machine-learning guide that helps you understand customers, frame decisions, and drive value Business Data Science reveals the best ways for utilizing machine learning (ML) to make the kind of data-driven decisions that lead to industry dominance. Whether you're a corporate leader, marketing executive, or business analyst, you'll find the information, insight, and tools you need to drive growth and profits in today's data-driven economy. You'll learn: -How ML works-How to use text-as-data for pricing decisions-How to utilize ML for A/B experiments-How to set up the best computing systems for their company's needs-And much more Business Data Science shows how to do data science right. It's about the exciting things being done around Big Data to run a flourishing business. It's about the precepts, principals, and best practices that you need know for best-in-class business data science. Armed with this first-of-its-kind guide, you'll be leaps and bounds ahead of your competition.
Editor Reviews
From the Back Cover Matt Taddy has written a thorough, thoughtful book on the statistics that underlie the use of big data. This is a fantastic resource, chock full of real applications, techniques, and insight. Unlike most machine learning texts, this book provides methods of extracting reliable understanding from data, addressing the problem that correlation is not causation. -- PRESTON MCAFEE , former Chief Economist and Corporate Vice President for Microsoft, and Professor and Executive Officer for the California Institute of Technology Drawing on his experience from his days as a star teacher at Chicago Booth and his work leading data science teams at Microsoft and Amazon, Matt Taddy has written a masterful book for MBAs, scientists, and engineers at modern companies. Weaving together concepts from statistics, machine learning, and social science, he has written a highly accessible text that is likely to become the standard in this area. -- GUIDO IMBENS , Professor of Economics at the Stanford Graduate School of Business, coauthor of Causal Inference for Statistics, Social, and Biomedical Sciences No one is better at combining insights from computer science, economics, and statistics to improve how businesses use their data. Everyone should read this book. -- JENS LUDWIG , McCormick Foundation Professor of Social Service Administration, Law and Public Policy and Director of the University of Chicago's Crime Lab Business Data Science brings together historically distinct disciplines to tackle a basic business reality: accurate predictions are not an end in themselves, but a means to taking high-quality actions. It reaches the current state of the art without requiring a strong data-science background. I recommend it to anyone interested in putting these ideas to practice. -- JON MCAULIFFE , Cofounder and Chief Investment Officer at The Voleon Group The most exciting data science book I have read in some time: current, modern, accessible, rigorous--and awesome. -- DIRK EDDELBUETTEL , R-package author and Clinical Professor of Statistics at University of Illinois