Artificial intelligence for marketing : practical applications / Jim Sterne. 6
By: Sterne, Jim, 4 0 16 [, author.] | [, ] |
Contributor(s): 5 6 [] |
Language: Unknown language code Summary language: Unknown language code Original language: Unknown language code Series: ; Wiley & SAS business seriesHoboken, New Jersey : John Wiley & Sons, Inc., [2017]46Edition: Description: 1 online resource (xix, 344 pages)Content type: text Media type: computer Carrier type: online resourceISBN: 9781119406341ISSN: 2Other title: 6 []Uniform titles: | | Subject(s): -- 2 -- 0 -- -- | -- 2 -- 0 -- 6 -- | 2 0 -- | -- -- 20 -- | | -- -- Marketing.;Artificial intelligence. -- -- 20 -- | -- -- -- 20 -- --Genre/Form: Electronic books. -- 2 -- Additional physical formats: Artificial intelligence for marketing.DDC classification: | 658.800285/63 LOC classification: | HF5415 | .S775 20172Other classification:| Item type | Current location | Home library | Collection | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|---|---|
| Book | PLM | PLM Circulation Section | Circulation-Circulating | HF5415 .S74 2017 (Browse shelf) | Available | C-EB154 |
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Includes bibliographical references and index.
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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Online resource; title from digital title page (viewed on August 31, 2017).
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