Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions
Taddy, Matt
- 出版商: McGraw-Hill Education
- 出版日期: 2019-08-21
- 售價: $1,710
- 貴賓價: 9.5 折 $1,625
- 語言: 英文
- 頁數: 352
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1260452778
- ISBN-13: 9781260452778
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相關分類:
Machine Learning、經濟學 Economy、Data Science
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相關翻譯:
數據科學與商業分析 用機器學習與統計學優化商業決策 (簡中版)
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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.
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.
作者簡介
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.