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Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions
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About Business Data Science: Combining Machine Learning
Product Description Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.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 problemsA wealth of real-world examples, including applications of text analysis, pricing and demand estimation, A/B experiments, and customer behavior analysisHow to move from correlation to causation and to use ML tools to make business decisionsAn example-driven education in scripting in R, including a wealth of R-code examples, giving you a launch pad for your own workScalable frameworks ideal for modern cloud computing environmentsWith 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. From the Publisher Matt Taddy was from 2008-2018 a Professor of Econometrics and Statistics at the University of Chicago Booth School of Business, where he developed their Data Science curriculum. Prior to and while at Chicago Booth, 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
