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

by Pedro Domingos

A thought-provoking and wide-ranging exploration of machine learning and the race to build computer intelligences as flexible as our own
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. In The Master Algorithm , Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner--the Master Algorithm--and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible.

Genres: Nonfiction, Science, Artificial Intelligence, Technology, Computer Science, Business, Programming

352 pages, Hardcover

First published September 8, 2015

About the author

I'm a professor emeritus of computer science and engineering at the University of Washington and the author of 2040 and The Master Algorithm. I'm a winner of the SIGKDD Innovation Award and the IJCAI John McCarthy Award, two of the highest honors in data science and AI. I'm a Fellow of the AAAS and AAAI, and I've received an NSF CAREER Award, a Sloan Fellowship, a Fulbright Scholarship, an IBM Faculty Award, several best paper awards, and other distinctions. I received an undergraduate degree (1988) and M.S. in Electrical Engineering and Computer Science (1992) from IST, in Lisbon, and an M.S. (1994) and Ph.D. (1997) in Information and Computer Science from the University of California at Irvine. I'm the author or co-author of over 200 technical publications in machine learning, data science, and other areas. I'm a member of the editorial board of the Machine Learning journal, co-founder of the International Machine Learning Society, and past associate editor of JAIR. I was program co-chair of KDD-2003 and SRL-2009, and I've served on the program committees of AAAI, ICML, IJCAI, KDD, NIPS, SIGMOD, UAI, WWW, and others. I've written for the Wall Street Journal, Spectator, Scientific American, Wired, and others. I helped start the fields of statistical relational AI, data stream mining, adversarial learning, machine learning for information integration, and influence maximization in social networks.

Reviews

[Mustafa Acungil]

Bazı temel bakış açılarını ve yaklaşımları vermesi açısından güzel bir kitaptı.
Ama tamamen yeni bir master algoritma geliştirmeye ve bunun nasıl yapılabileceğine odaklı bir kitap.
Machine Learning'le yeni algoritmalar geliştirme seviyesinde ilgilenenler için ilgi çekici olabilir.
Machine Learning'i kullanmak isteyenler için ise her ne kadar bazı bölümleri yararlı olsa da geneli kafa karıştırıcı ve gereksiz olarak düşünülebilir.

[Yusuf Ziya]

Okuması eğlenceli olduğu kadar bilgi birikimi isteyen bir kitap. Kapakta "Yapay öğrenme hayatımızı nasıl değiştirecek?" diye sorarken başta acaba hayatımıza neler olacak diye düşünürken aslında bu "nasıl?" sorusunun teknik olarak bunu nasıl becerebileceğine işaret ettiğini anlıyorsunuz.