The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World

by Pedro Domingos

Overview

Algorithms increasingly run our lives. They find books, movies, jobs, and dates for us, manage our investments, and discover new drugs. More and more, these algorithms work by learning from the trails of data we leave in our newly digital world. Like curious children, they observe us, imitate, and experiment. And in the world’s top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask.

Machine learning is the automation of discovery—the scientific method on steroids—that enables intelligent robots and computers to program themselves. No field of science today is more important yet more shrouded in mystery. Pedro Domingos, one of the field’s leading lights, lifts the veil for the first time to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He charts a course through machine learning’s five major schools of thought, showing how they turn ideas from neuroscience, evolution, psychology, physics, and statistics into algorithms ready to serve you. Step by step, he assembles a blueprint for the future universal learner—the Master Algorithm—and discusses what it means for you, and for the future of business, science, and society.

If data-ism is today’s rising philosophy, this book will be its bible. The quest for universal learning is one of the most significant, fascinating, and revolutionary intellectual developments of all time. A groundbreaking book, The Master Algorithm is the essential guide for anyone and everyone wanting to understand not just how the revolution will happen, but how to be at its forefront.

Product Details

ISBN-13:	9780465061921
Publisher:	Basic Books
Publication date:	09/22/2015
Sold by:	Hachette Digital, Inc.
Format:	eBook
Pages:	352
Sales rank:	656,284
File size:	6 MB

About the Author

Pedro Domingos is a professor of computer science at the University of Washington. He is a winner of the SIGKDD Innovation Award, the highest honor in data science. A fellow of the Association for the Advancement of Artificial Intelligence, he lives near Seattle.

Table of Contents

1. The Machine Learning Revolution
2. The Master Algorithm
3. Hume's Problem of Induction
4. How Does Your Brain Learn?
5. Evolution: Nature's Learning Algorithm
6. In the Church of the Reverend Bayes
7. You Are What You Resemble
8. Learning Without a Teacher
9. The Pieces of the Puzzle Fall into Place
10. This Is the World on Machine Learning

Editorial Reviews

"Wonderfully erudite, humorous, and easy to read."—KDNuggets

"Pedro Domingos demystifies machine learning and shows how wondrous and exciting the future will be."—Walter Isaacson, New York Times bestselling author of Steve Jobs, The Innovators, and The Code Breaker

"An impressive and wide-ranging work that covers everything from the history of machine learning to the latest technical advances in the field."—Daily Beast

"Domingos writes with verve and passion."—New Scientist

"Unlike other books that proclaim a bright future, this one actually gves you what you need to understand the changes that are coming."—Peter Norvig, Director of Research, Google andcoauthor of Artificial Intelligence: A Modern Approach

"Domingos is the perfect tour guide from whom you will learn everything you need to know about this exciting field, and a surprising amount about sience and philosophy as well."—Duncan Watts, Principal Researcher, Microsoft Research, and author of Six Degrees and Everything Is Obvious *Once You Know the Answer

"[The Master Algorithm] does a good job of examining the field's five main techniques.... The subject is meaty and the author...has a knack for introducing concepts at the right moment."—The Economist

"Domingos is a genial and amusing guide, who sneaks us around the backstage areas of the science in order to witness the sometimes personal (and occasionally acrimonious) tenor of research on the subject in recent decades."—Times Higher Education

"An exhilarating venture into groundbreaking computer science."—Booklist, starred review

"[An] enthusiastic but not dumbed-down introduction to machine learning...lucid and consistently informative.... With wit, vision, and scholarship, Domingos decribes how these scientists are creating programs that allow a computer to teach itself. Readers...will discover fascinating insights."
—Kirkus Reviews

"This book is a must have to learn machine learning without equation. It will help you get the big picture of the several learning paradigms. Finally, the provocative idea is not only intriguing, but also very well argued."—Data Mining Research

"If you are interested in a crash course on the enigmatic field of machine learning and the challenges for AI practitioners that lie ahead, this book is a great read."—TechCast Global

"This book is a sheer pleasure, mixed with education. I am recommending it to all my students, those who studied machine learning, those who are about to do it and those who are about to teach it."—Judea Pearl, author of The Book of Why, and professor of computer science, UCLA and winner of the A. M. Turing Award

"Machine learning is the single most transformative technology that will shape our lives over the next fifteen years. This book is a must-read—a bold and beautifully written new framework for looking into the future."—Geoffrey Moore, author of Crossing the Chasm

"Machine learning is a fascinating world never before glimpsed by outsiders. Pedro Domingos initiates you to the mysterious languages spoken by its five tribes, and invites you to join in his plan to unite them, creating the most powerful technology our civilization has ever seen."—Sebastian Seung, professor, Princeton, and author of Connectome

"A delightful book by one of the leading experts in the field. If you wonder how AI will change your life, read this book."—Sebastian Thrun, research professor, Stanford, Google Fellow and Inventor of the Self-Driving Car

"This is an incredibly important and useful book. Machine learning is already critical to your life and work, and will only become more so. Finally, Pedro Domingos has written about it in a clear and understandable fashion."—Thomas H. Davenport, Distinguished Professor, Babson College and author of Competing on Analytics and Big Data @ Work span

"Machine learning, known in commercial use as predictive analytics, is changing the world. This riveting, far-reaching, and inspiring book introduces the deep scientific concepts to even non-technical readers, and yet also satisfies experts with a fresh, profound perspective that reveals the most promising research directions. It's a rare gem indeed."—Eric Siegel, founder of Predictive Analytics World and author of Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die

From the Publisher

2015-06-08
Traditionally, the only way to make a computer execute a task is to write precise instructions: an algorithm. As the author notes in this enthusiastic but not dumbed-down introduction to machine learning, it is impossible to "write a program to tell a computer how to drive a car or decipher handwriting, but if we give enough examples to a computer running a learning algorithm, it will figure out how to do it on its own." The ultimate learning program, writes Domingos (Computer Science/Univ. of Washington), is the master algorithm, and the process is well underway to allow computers to function creatively. Data alone is not enough. Defeating the world's greatest chess or Jeopardy players was a matter of brute force, but simpler computers running learning programs already beat talent scouts in baseball, connoisseurs in wine tasting, and doctors in disease diagnosis. Though lucid and consistently informative, Domingos' explanation of how a variety of scientific schools approaches the master algorithm requires close attention from readers. Symbolists believe that intelligence emerges from manipulating symbols, just as mathematicians solve equations by replacing expressions with other expressions. Connectionists try to reverse-engineer the brain. Evolutionaries write programs that change in ways similar to natural selection. Bayesians know that all learned knowledge is uncertain, so they emphasize 18th-century English clergyman Thomas Bayes' theorem, which can handle probabilistic inference. Finally, analogizers search for similarities in data and write code that combines them to make new predictions. "Armed with your new understanding of machine learning," writes the author, "you're in a much better position to think about issues like privacy and data sharing, the future of work, robot warfare, and the promise and peril of AI." With wit, vision, and scholarship, Domingos describes how these scientists are creating programs that allow a computer to teach itself. Readers unfamiliar with logic and computer theory will have a difficult time, but those who persist will discover fascinating insights.

Kirkus Reviews