The AI playbook
MIT Press (Verlag)
978-0-262-04890-3 (ISBN)
“Eric Siegel delivers a robust primer on machine learning, the key mechanism in AI. A forward-looking, practical book and a must-read for anyone in the information economy.”
—Scott Galloway, NYU Stern Professor of Marketing; bestselling author of The Four
“An antidote to today’s relentless AI hype—why some AI initiatives thrive while others fail and what it takes for companies and people to succeed.”
—Charles Duhigg, author of bestsellers The Power of Habit and Smarter Faster Better
The greatest tool is the hardest to use. Machine learning is the world’s most important general-purpose technology—but it’s notoriously difficult to launch. Outside Big Tech and a handful of other leading companies, machine learning initiatives routinely fail to deploy, never realizing value. What’s missing? A specialized business practice suitable for wide adoption. In The AI Playbook, bestselling author Eric Siegel presents the gold-standard, six-step practice for ushering machine learning projects from conception to deployment. He illustrates the practice with stories of success and of failure, including revealing case studies from UPS, FICO, and prominent dot-coms. This disciplined approach serves both sides: It empowers business professionals, and it establishes a sorely needed strategic framework for data professionals.
Beyond detailing the practice, this book also upskills business professionals—painlessly. It delivers a vital yet friendly dose of semi-technical background knowledge that all stakeholders need to lead or participate in machine learning projects, end to end. This puts business and data professionals on the same page so that they can collaborate deeply, jointly establishing precisely what machine learning is called upon to predict, how well it predicts, and how its predictions are acted upon to improve operations. These essentials make or break each initiative—getting them right paves the way for machine learning’s value-driven deployment.
What kind of AI does this book cover? The buzzword AI can mean many things, but this book is about machine learning, which is a central basis for—and what many mean by—AI. To be specific, this book covers the most vital use cases of machine learning, those designed to improve a wide range of business operations.
Eric Siegel is a leading consultant and former Columbia University and UVA Darden professor. He is the founder of the long-running Machine Learning Week conference series, a frequent keynote speaker, and author of the bestselling Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die.
Contents
Series Foreword ix
Foreword by Morgan Vawter xi
Preface: A Brief History of Why Machine Learning Projects Stall xv
Optional FAQ: What This Book Is about and Who It’s For xxi
Introduction 1
0 BizML: Six Steps to Machine Learning Deployment 21
1 Value: Establish the Deployment Goal 49
2 Target: Establish the Prediction Goal 63
3 Performance: Establish the Evaluation Metrics 81
4 Fuel: Prepare the Data 113
5 Algorithm: Train the Model 141
6 Launch: Deploy the Model 169
BizML Cheat Sheet 195
Conclusion: ML’s Elevator Pitch, Staff, Timeline, Upkeep, and Ethics 197
Acknowledgments 213
About the Author 217
Index 219
| Erscheinungsdatum | 01.02.2024 |
|---|---|
| Zusatzinfo | Illustrationen |
| Verlagsort | [Cambridge] |
| Sprache | englisch |
| Maße | 152 x 229 mm |
| Einbandart | gebunden |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Naturwissenschaften | |
| Wirtschaft ► Betriebswirtschaft / Management ► Unternehmensführung / Management | |
| Wirtschaft ► Volkswirtschaftslehre | |
| ISBN-10 | 0-262-04890-6 / 0262048906 |
| ISBN-13 | 978-0-262-04890-3 / 9780262048903 |
| Zustand | Neuware |
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