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

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Item specifics

Condition
Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See all condition definitionsopens in a new window or tab
ISBN
9780262048903
Category

About this product

Product Identifiers

Publisher
MIT Press
ISBN-10
0262048906
ISBN-13
9780262048903
eBay Product ID (ePID)
14060616280

Product Key Features

Book Title
Ai PlayBook : Mastering the Rare Art of Machine Learning Deployment
Number of Pages
256 Pages
Language
English
Topic
Social Aspects, Intelligence (Ai) & Semantics, Commerce, Management
Publication Year
2024
Genre
Computers, Technology & Engineering, Business & Economics
Author
Eric Siegel
Book Series
Management on the Cutting Edge Ser.
Format
Hardcover

Dimensions

Item Height
1.1 in
Item Weight
17.1 Oz
Item Length
9.3 in
Item Width
6.4 in

Additional Product Features

Intended Audience
Trade
LCCN
2023-017997
Reviews
"In his new book The AI Playbook , Eric Siegel, a leading consultant and former Columbia University professor, helps bridge the gap between ML as a science and a business practice. Siegel delves into the reasons ML projects fail and provides a framework for implementing machine learning in business." -- TechTalks
TitleLeading
The
Table Of Content
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
Synopsis
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; 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, aka predictive AI 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. A note from the author: The buzzword AI can mean many things, but this book is about the most vital use cases of machine learning , those designed to improve large-scale business operations--aka predictive AI or predictive analytics., 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; 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, aka predictive AI 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. A note from the author- The buzzword AI can mean many things, but this book is about the most vital use cases of machine learning , those designed to improve large-scale business operations-aka predictive AI or predictive analytics.
LC Classification Number
HF5548.2.S44865 2024

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