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Da: GreatBookPrices, Columbia, MD, U.S.A.
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Da: INDOO, Avenel, NJ, U.S.A.
EUR 62,00
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Da: INDOO, Avenel, NJ, U.S.A.
EUR 62,08
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EUR 61,85
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Da: Majestic Books, Hounslow, Regno Unito
EUR 64,70
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Da: Revaluation Books, Exeter, Regno Unito
EUR 59,29
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Aggiungi al carrelloHardcover. Condizione: Brand New. 323 pages. 9.25x6.25x1.00 inches. In Stock.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 64,19
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Da: Chiron Media, Wallingford, Regno Unito
EUR 59,00
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 61,84
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Hardcover. Condizione: 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.
Lingua: Inglese
Editore: Information technology: general issues, 2023
ISBN 10: 0262048612 ISBN 13: 9780262048613
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
EUR 67,99
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Da: Chiron Media, Wallingford, Regno Unito
EUR 64,20
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Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 72,98
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 69,26
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 71,60
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Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 69,77
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Aggiungi al carrelloHardback. Condizione: New. New copy - Usually dispatched within 4 working days.
Lingua: Inglese
Editore: Information technology: general issues, 2023
ISBN 10: 0262048612 ISBN 13: 9780262048613
Da: Kennys Bookstore, Olney, MD, U.S.A.
Condizione: New. 2023. Hardcover. . . . . . Books ship from the US and Ireland.
Da: La Casa de los Libros, Castellgali, B, Spagna
EUR 45,70
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EUR 78,94
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Aggiungi al carrelloHardcover. Condizione: 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 our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.