The AI Playbook: Mastering the Rare Art of Machine Learning Deployment

Eric Siegel's book "The AI Playbook" provides a practical guide to capitalizing on machine learning, a crucial technology in AI. It offers a six-step practice for launching machine learning projects, with case studies from successful and failed initiatives. The book empowers business professionals and establishes a strategic framework for data professionals, helping them collaborate effectively and ensure machine learning's value-driven deployment.

Format: Hardback
Length: 248 pages
Publication date: 06 February 2024
Publisher: MIT Press Ltd

Eric Siegel, the bestselling author of "The AI Playbook," has written a new book that explains how to capitalize on machine learning. The book is a primer on machine learning, the key mechanism in AI, and is a must-read for anyone in the information economy. Siegel's book provides a robust primer on machine learning, the key mechanism in AI. It is a forward-looking, practical book that is a must-read for anyone in the information economy. Scott Galloway, NYU Stern Professor of Marketing and bestselling author of "The Four," describes the book as an antidote to today's relentless AI hype. Charles Duhigg, author of bestsellers "The Power of Habit" and "Smarter Faster Better," describes the book as an antidote to today's relentless AI hype. The greatest tool is the hardest to use, and machine learning is the world's most important general-purpose technology. However, it is notoriously difficult to launch. Outside of Big Tech and a handful of other leading companies, machine learning initiatives routinely fail to deploy, never realizing value. What is 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, also known as predictive AI projects, from conception to deployment. He illustrates the practice with stories of success and failure, including revealing case studies from UPS, FICO, and prominent dot-coms. This disciplined approach serves both sides: It empowers business professionals and 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.

Weight: 488g
Dimension: 161 x 236 x 26 (mm)
ISBN-13: 9780262048903