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        Computers / Data Science / General

        Showing results 1-10 of 17

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        ‹12›
        Data Rules

        Data Rules

        Data Rules

        Reinventing the Market Economy

        by Cristina Alaimo and Jannis Kallinikos

        Foreword by Michael Power

        ISBN: 9780262547932

        Publisher: The MIT Press

        Pub Date: June 4, 2024

        A new social science framework for studying the unprecedented social and economic restructuring driven by digital data.
        Counting Feminicide

        Counting Feminicide

        Counting Feminicide

        Data Feminism in Action

        by Catherine D'Ignazio

        ISBN: 9780262048873

        Publisher: The MIT Press

        Pub Date: April 30, 2024

        Why grassroots data activists in Latin America count feminicide—and how this vital social justice work challenges mainstream data science.
        Critical Data Literacies

        Critical Data Literacies

        Critical Data Literacies

        Rethinking Data and Everyday Life

        by Luci Pangrazio and Neil Selwyn

        ISBN: 9780262546829

        Publisher: The MIT Press

        Pub Date: November 21, 2023

        A guide to everything you need to understand to navigate a world increasingly governed by data.
        Data Paradoxes

        Data Paradoxes

        Data Paradoxes

        The Politics of Intensified Data Sourcing in Contemporary Healthcare

        by Klaus Hoeyer

        ISBN: 9780262545419

        Publisher: The MIT Press

        Pub Date: April 18, 2023

        Why healthcare cannot—and should not—become data-driven, despite the many promises of intensified data sourcing.
        Beyond Data

        Beyond Data

        Beyond Data

        Reclaiming Human Rights at the Dawn of the Metaverse

        by Elizabeth M. Renieris

        ISBN: 9780262047821

        Publisher: The MIT Press

        Pub Date: February 7, 2023

        Why laws focused on data cannot effectively protect people—and how an approach centered on human rights offers the best hope for preserving human dignity and autonomy in a cyberphysical world.
        There Are No Facts

        There Are No Facts

        There Are No Facts

        Attentive Algorithms, Extractive Data Practices, and the Quantification of Everyday Life

        by Mark Shepard

        ISBN: 9780262047470

        Publisher: The MIT Press

        Pub Date: November 22, 2022

        The entanglements of people and data, code and space, knowledge and power: how data and algorithms shape the world—and shape us within that world.
        The Alienation of Fact

        The Alienation of Fact

        The Alienation of Fact

        Digital Educational Privatization, AI, and the False Promise of Bodies and Numbers

        by Kenneth J. Saltman

        ISBN: 9780262544368

        Publisher: The MIT Press

        Pub Date: November 22, 2022

        An investigation of the role of educational privatization and technology in the crises of truth and agency.
        Digital Oil

        Digital Oil

        Digital Oil

        Machineries of Knowing

        by Eric Monteiro

        ISBN: 9780262544672

        Publisher: The MIT Press

        Pub Date: November 8, 2022

        How is digitalization of the offshore oil industry fundamentally changing how we understand work and ways of knowing?
        Everyday Adventures with Unruly Data

        Everyday Adventures with Unruly Data

        Everyday Adventures with Unruly Data

        by Melanie Feinberg

        ISBN: 9780262544405

        Publisher: The MIT Press

        Pub Date: October 11, 2022

        Paired informal and scholarly essays show how everyday events reveal fundamental concepts of data, including its creation, aggregation, management, and use.
        Dataset Shift in Machine Learning

        Dataset Shift in Machine Learning

        Dataset Shift in Machine Learning

        Edited by Joaquin Quiñonero-Candela, Masashi Sugiyama, Anton Schwaighofer and Neil D. Lawrence

        ISBN: 9780262545877

        Publisher: The MIT Press

        Pub Date: June 7, 2022

        An overview of recent efforts in the machine learning community to deal with dataset and covariate shift, which occurs when test and training inputs and outputs have different distributions.
        ‹12›

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