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Business data science : combining machine learning and economics to optimize, automate, and accelerate business decisions /
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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York :
McGraw-Hill Education,
[2019]
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| Colección: | McGraw-Hill's AccessEngineering.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Taddy, Matt, |e author. | |
| 245 | 1 | 0 | |a Business data science : |b combining machine learning and economics to optimize, automate, and accelerate business decisions / |c Matt Taddy. |
| 264 | 1 | |a New York : |b McGraw-Hill Education, |c [2019] | |
| 264 | 4 | |c ©2019 | |
| 300 | |a 1 online resource (352 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 490 | 0 | |a McGraw-Hill's AccessEngineering | |
| 500 | |a Available through AccessEngineering. | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Cover -- Title Page -- Copyright Page -- Dedication -- Contents -- 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 | |
| 520 | |a 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: " se the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling " nderstand how use ML tools in real world business problems, where causation matters more that correlation " olve 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 | ||
| 588 | 0 | |a Description based on resource viewed on July 15, 2023. | |
| 542 | |f Copyright © McGraw-Hill 2019 |g 2019 | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Decision making |x Econometric models. | |
| 650 | 0 | |a Machine learning. | |
| 650 | 6 | |a Prise de décision |x Modèles économétriques. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 7 | |a information technology. |2 aat | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x General. |2 bisacsh | |
| 650 | 7 | |a Decision making |x Econometric models. |2 fast |0 (OCoLC)fst00889042 | |
| 650 | 7 | |a Machine learning. |2 fast |0 (OCoLC)fst01004795 | |
| 650 | 7 | |a Data Science |2 gnd | |
| 650 | 7 | |a Entscheidungsfindung |2 gnd | |
| 650 | 7 | |a Maschinelles Lernen |2 gnd | |
| 650 | 7 | |a Unternehmen |2 gnd | |
| 710 | 2 | |a McGraw-Hill Higher Education (Firm) | |
| 776 | 0 | 8 | |i Print version: |a Taddy, Matt. |t Business data science. |b 1 Edition. |d New York : McGraw-Hill Education, 2019 |z 9781260452778 |w (DLC) 2018052621 |w (OCoLC)1055264877 |
| 830 | 0 | |a McGraw-Hill's AccessEngineering. | |
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