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The AI Playbook
- Mastering the Rare Art of Machine Learning Deployment (Management on the Cutting Edge)
- ナレーター: Eric Siegel
- 再生時間: 9 時間 20 分
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批評家のレビュー
“Set aside the hype and focus on getting things to work in practice. This is a crisp, necessary, and deeply helpful guide to getting things done with AI. Essential reading.”
—Mustafa Suleyman, Cofounder and CEO, Inflection AI; author of The Coming Wave
“In this book, Eric brings machine learning to life and provides a roadmap for how to operationalize it in the real world.”
—Will Lansing, CEO, FICO
“There's a big difference between theory and practice. This is the guide that tells you how to really make data come alive through machine learning.”
—DJ Patil, General Partner, Great Point Ventures and Former U.S. Chief Data Scientist
あらすじ・解説
In his bestselling first book, Eric Siegel explained how machine learning works. Now, in The AI Playbook, he shows how to capitalize on it.
"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 and 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.
PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.