Description

Book Synopsis
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, youâll find the information, insight, and tools you need to flourish in todayâs data-driven economy. Youâll learn how to: 


â Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and

Table of 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

Business Data Science Combining Machine Learning

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    A Hardback by Matt Taddy

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    RRP £29.99 – you save £6.00 (20%)

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      Book details

      Publisher McGraw-Hill Education
      Published 18 August 2019
      ISBN-13 9781260452778
      978-1260452778
      ISBN-10 1260452778
      Also in:
      Business, Finance & Law Business and Management Management decision making

      Description

      Book Synopsis
      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, youâll find the information, insight, and tools you need to flourish in todayâs data-driven economy. Youâll learn how to: 


      â Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and

      Table of 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

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