Items related to Fairness and Machine Learning: Limitations and Opportunities...
Fairness and Machine Learning: Limitations and Opportunities (Adaptive Computation and Machine Learning series) - Hardcover
- PublisherThe MIT Press
- Publication date2023
- ISBN 10 0262048612
- ISBN 13 9780262048613
- BindingHardcover
- LanguageEnglish
- Number of pages340
- Rating
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Fairness and Machine Learning: Limitations and Opportunities (Adaptive Computation and Machine Learning series)
Seller: Bellwetherbooks, McKeesport, PA, U.S.A.
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hardcover. Condition: Fair. Bruise/tear to spine and book comp creased. Seller Inventory # MIT-HC-D-0262048612
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Fairness and Machine Learning: Limitations and Opportunities (Adaptive Computation and Machine Learning series)
Seller: Big River Books, Powder Springs, GA, U.S.A.
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Condition: like_new. This book is in Like New condition. It is unused, but has a remainder mark on the edge of the pages. Otherwise it is a new book. Seller Inventory # BRV.0262048612.LN
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Fairness and Machine Learning: Limitations and Opportunities (Adaptive Computation and Machine Learning series)
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Fairness and Machine Learning : Limitations and Opportunities
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Fairness and Machine Learning Limitations and Opportunities Format: Hardcover
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Condition: As New. Unread copy in mint condition. Seller Inventory # RH9780262048613
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Fairness and Machine Learning : Limitations and Opportunities
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Fairness and Machine Learning Limitations and Opportunities Format: Hardcover
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Fairness and Machine Learning
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Fairness and Machine Learning (Hardcover)
Seller: Grand Eagle Retail, Fairfield, OH, U.S.A.
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Hardcover. Condition: new. Hardcover. An introduction to the intellectual foundations and practical utility of the recent work on fairness and machine learning.An introduction to the intellectual foundations and practical utility of the recent work on fairness and machine learning.Fairness and Machine Learning introduces advanced undergraduate and graduate students to the intellectual foundations of this recently emergent field, drawing on a diverse range of disciplinary perspectives to identify the opportunities and hazards of automated decision-making. It surveys the risks in many applications of machine learning and provides a review of an emerging set of proposed solutions, showing how even well-intentioned applications may give rise to objectionable results. It covers the statistical and causal measures used to evaluate the fairness of machine learning models as well as the procedural and substantive aspects of decision-making that are core to debates about fairness, including a review of legal and philosophical perspectives on discrimination. This incisive textbook prepares students of machine learning to do quantitative work on fairness while reflecting critically on its foundations and its practical utility. Introduces the technical and normative foundations of fairness in automated decision-making. Covers the formal and computational methods for characterizing and addressing problems. Provides a critical assessment of their intellectual foundations and practical utility. Features rich pedagogy and extensive instructor resources "This book offers a critical view on the current practice of machine learning, as well as proposed technical fixes for achieving fairness in automated decisionmaking"-- Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780262048613
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Fairness and Machine Learning
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
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HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # H8-9780262048613
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