Business data science : combining machine learning and economics to optimize, automate, and accelerate business decisions

書誌事項

Business data science : combining machine learning and economics to optimize, automate, and accelerate business decisions

Matt Taddy

McGraw-Hill Education, c2019

  • : hardback

大学図書館所蔵 件 / 24

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注記

Includes bibliographical references (p. 313-320) and index

内容説明・目次

内容説明

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 The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science. Whether you are a business leader with a desire to go deep on data, or an engineer who wants to learn how to apply Machine Learning to business problems, you'll find the information, insight, and tools you need to flourish in today's data-driven economy. You'll learn how to: *Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling*Understand how use ML tools in real world business problems, where causation matters more that correlation*Solve data science programs by scripting in the R programming language Today's business landscape is driven by data and constantly shifting. Companies live and die on their ability to make and implement the right decisions quickly and effectively. Business Data Science is about doing 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.

目次

Preface Introduction 1 Uncertainty 2 Regression 3 Regularization 4 Classification 5 Experiments 6 Controls 7 Factorization 8 Text as Data 9 Nonparametrics 10 Artificial Intelligence Bibliography Index

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