Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions - Hardcover

Taddy, Matt

Hardcover

ISBN 10: 1260452778 ISBN 13: 9781260452778

Publisher: McGraw Hill, 2019

Synopsis

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Use machine learning to understand your customers, frame decisions, and drive value

  

Spreadsheet models and pivot tables were once the cutting-edge tools of business analysis. But the Big Data revolution has changed everything. Tasks that once required armies of business analysts are being automated and scaled with software, allowing decision makers to go deep into the data to understand how their business is running and what their customers want. This has led to a new superstar job class: the Business Data Scientist who is able to combine science and engineering tools with business and economic context to build data analyses that drive better decisions.

Matt Taddy, developer of the Big Data curriculum at the University of Chicago Booth School of Business, has made a career of training students to use economic principles to connect business decisions to massive data. Business Data Science is an essential primer for those who want to use cutting-edge machine learning to have a real impact on the direction of their business.

With Business Data Science, readers will learn:

• The key ingredients that make ML work, without getting lost in the hype, and a playbook for how ML and AI can be used to solve business problems
• A wealth of real-world examples, including applications of text analysis, pricing and demand estimation, A/B experiments, and customer behavior analysis
• How to move from correlation to causation and to use ML tools to make business decisions
• An example-driven education in scripting in R, including a wealth of R-code examples, giving you a launch pad for your own work
• Scalable frameworks ideal for modern cloud computing environments

With Business Data Science you have everything you need to connect business problems to data and drive decisions with data analysis. You'll understand your customers better, make more informed business decisions, achieve maximum value--and thrive in today's data-driven economy.

About this title

About the Author

Matt Taddy was a Professor of Econometrics and Statistics from 2008-2018 at the University of Chicago Booth School of Business, where he developed their Data Science curriculum. He has also worked in a variety of industry positions including as a Principal Researcher at Microsoft and a research fellow at eBay. He left Chicago in 2018 to join Amazon as a Vice President.

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

Edition details

• Publisher: McGraw Hill
• Publication date: 2019
• Language: English
• ISBN 10: 1260452778
• ISBN 13: 9781260452778
• Binding: Hardcover
• Edition number: 1
• Number of pages: 352