Artificial intelligence for marketing : practical applications / Jim Sterne.
Material type: TextSeries: Wiley and SAS business seriesPublication details: Hoboken, New Jersey : John Wiley & Sons, Inc., [2017]Description: 1 online resource (xix, 344 pages)ISBN: 9781119406365; 1119406366; 9781119406341; 111940634X; 9781119406372; 1119406374Subject(s): Marketing | Artificial intelligence | BUSINESS & ECONOMICS -- Industrial Management | BUSINESS & ECONOMICS -- Management | BUSINESS & ECONOMICS -- Management Science | BUSINESS & ECONOMICS -- Organizational Behavior | Artificial intelligence | MarketingOnline resources: Wiley Online LibraryItem type | Current library | Call number | Status | Date due | Barcode | Item holds |
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e-Books | Central Library, Sikkim University | Not for loan | E-2883 |
Cover ; Title Page ; Copyright ; Contents; Foreword; Preface; Acknowledgments; Chapter 1: Welcome to the Future ; Welcome to Autonomic Marketing ; Welcome to Artificial Intelligence for Marketers ; Detect ; Decide ; Develop ; Whom Is This Book For? ; The Bright, Bright Future.
Is AI So Great if It's So Expensive? What's All This AI Then? ; The AI Umbrella ; The Machine that Learns ; Guess the Animal ; The Machine that Programs Itself ; Are We There Yet? ; AI-pocalypse; The AI that Ate the Earth ; Intentional Consequences Problem ; Unintended Consequences.
Will a Robot Take Your Job? Machine Learning's Biggest Roadblock ; Machine Learning's Greatest Asset ; How We Used to Dive into Data ; Variety of Data Is the Spice of Life ; Open Data ; Data for Sale ; But Wait-There's More; A Collaboration of Datasets ; A Customer Data Taxonomy.
Are We Really Calculable? Notes ; Chapter 2: Introduction to Machine Learning ; Three Reasons Data Scientists Should Read This Chapter ; Every Reason Marketing Professionals Should Read This Chapter ; We Think We're So Smart ; Define Your Terms ; All Models Are Wrong ; Useful Models.
Too Much to Think About Machines Are Big Babies ; Where Machines Shine ; High Cardinality ; High Dimensionality ; Strong versus Weak AI ; The Right Tool for the Right Job ; Classification versus Regression ; Supervised Machine Learning ; Unsupervised Learning ; Neural Networks.
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