Machine learners : archaeology of a data practice / Adrian Mackenzie.
Material type:
TextPublisher: Cambridge, Massachusetts : The MIT Press, [2017]Copyright date: ©2017Description: xvi, 252 pages : illustrations (black and white) ; 24 cmContent type: text | still image Media type: unmediated Carrier type: volumeISBN: 9780262036825 (hbk.) :Subject(s): Information theory | Machine learning -- Philosophy | Electronic data processing -- Philosophy | General | GeneralDDC classification: 003.5'4 Summary: Machine learning - programming computers to learn from data - has spread across scientific disciplines, media, entertainment, and government. Medical research, autonomous vehicles, credit transaction processing, computer gaming, recommendation systems, finance, surveillance, and robotics use machine learning. Machine learning devices (sometimes understood as scientific models, sometimes as operational algorithms) anchor the field of data science. They have also become mundane mechanisms deeply embedded in a variety of systems and gadgets. In contexts from the everyday to the esoteric, machine learning is said to transform the nature of knowledge. Adrian Mackenzie investigates whether machine learning also transforms the practice of critical thinking.
| Item type | Current library | Home library | Shelving location | Class number | Status | Date due | Barcode | Item reservations | |
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Paul Hamlyn Library | Paul Hamlyn Library | Floor 1 | 003.54 MAC (Browse shelf(Opens below)) | Available | 06609635 |
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| 003.54 INF Information design / | 003.54 INF Information design / | 003.54 LIM Visual complexity : mapping patterns of information / | 003.54 MAC Machine learners : archaeology of a data practice / | 003.857 SMI Chaos : a very short introduction / | 004 DIG Digital literacies : concepts, policies and practices / | 004 DIG Digital literacies : concepts, policies and practices / |
Includes bibliographical references and index.
Machine learning - programming computers to learn from data - has spread across scientific disciplines, media, entertainment, and government. Medical research, autonomous vehicles, credit transaction processing, computer gaming, recommendation systems, finance, surveillance, and robotics use machine learning. Machine learning devices (sometimes understood as scientific models, sometimes as operational algorithms) anchor the field of data science. They have also become mundane mechanisms deeply embedded in a variety of systems and gadgets. In contexts from the everyday to the esoteric, machine learning is said to transform the nature of knowledge. Adrian Mackenzie investigates whether machine learning also transforms the practice of critical thinking.
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