Grant fleming peter c bruce (12 resultados)
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Librería: HPB-Red, Dallas, TX, Estados Unidos de AmericaHPB-Red
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EUR 9,87
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Paperback. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.
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Librería: Lakeside Books, Benton Harbor, MI, Estados Unidos de AmericaLakeside Books
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EUR 24,60
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Condición: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books.
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Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA
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EUR 31,46
Gastos de envío gratisSe envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Paperback. Condición: New. Explore the most serious prevalent ethical issues in data science with this insightful new resource The increasing popularity of data science has resulted in numerous well-publicized cases of bias, injustice, and discrimination. The widespread deployment of "Black box" algorithms that are difficult or…impossible to understand and explain, even for their developers, is a primary source of these unanticipated harms, making modern techniques and methods for manipulating large data sets seem sinister, even dangerous. When put in the hands of authoritarian governments, these algorithms have enabled suppression of political dissent and persecution of minorities. To prevent these harms, data scientists everywhere must come to understand how the algorithms that they build and deploy may harm certain groups or be unfair. Responsible Data Science delivers a comprehensive, practical treatment of how to implement data science solutions in an even-handed and ethical manner that minimizes the risk of undue harm to vulnerable members of society. Both data science practitioners and managers of analytics teams will learn how to: Improve model transparency, even for black box modelsDiagnose bias and unfairness within models using multiple metricsAudit projects to ensure fairness and minimize the possibility of unintended harm Perfect for data science practitioners, Responsible Data Science will also earn a spot on the bookshelves of technically inclined managers, software developers, and statisticians.
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Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de AmericaRarewaves USA
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 33,09
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 8 disponibles
Paperback. Condición: New. Explore the most serious prevalent ethical issues in data science with this insightful new resource The increasing popularity of data science has resulted in numerous well-publicized cases of bias, injustice, and discrimination. The widespread deployment of "Black box" algorithms that are difficult or…impossible to understand and explain, even for their developers, is a primary source of these unanticipated harms, making modern techniques and methods for manipulating large data sets seem sinister, even dangerous. When put in the hands of authoritarian governments, these algorithms have enabled suppression of political dissent and persecution of minorities. To prevent these harms, data scientists everywhere must come to understand how the algorithms that they build and deploy may harm certain groups or be unfair. Responsible Data Science delivers a comprehensive, practical treatment of how to implement data science solutions in an even-handed and ethical manner that minimizes the risk of undue harm to vulnerable members of society. Both data science practitioners and managers of analytics teams will learn how to: Improve model transparency, even for black box modelsDiagnose bias and unfairness within models using multiple metricsAudit projects to ensure fairness and minimize the possibility of unintended harm Perfect for data science practitioners, Responsible Data Science will also earn a spot on the bookshelves of technically inclined managers, software developers, and statisticians.
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Librería: Majestic Books, Hounslow, , Reino UnidoMajestic Books
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EUR 34,88
Envío por EUR 7,54Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 3 disponibles
Condición: New.
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Librería: Revaluation Books, Exeter, , Reino UnidoRevaluation Books
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EUR 34,94
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Paperback. Condición: Brand New. 304 pages. 9.00x7.25x0.75 inches. In Stock.
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Librería: Chiron Media, Wallingford, , Reino UnidoChiron Media
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EUR 33,21
Envío por EUR 17,96Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Paperback. Condición: New.
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 49,76
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Condición: New.
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Librería: Ubiquity Trade, Miami, FL, Estados Unidos de AmericaUbiquity Trade
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EUR 61,11
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Condición: New. Brand new! Please provide a physical shipping address.
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Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de AmericaRarewaves USA United
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 34,76
Envío por EUR 43,76Se envía dentro de Estados Unidos de AmericaCantidad disponible: 8 disponibles
Paperback. Condición: New. Explore the most serious prevalent ethical issues in data science with this insightful new resource The increasing popularity of data science has resulted in numerous well-publicized cases of bias, injustice, and discrimination. The widespread deployment of "Black box" algorithms that are difficult or…impossible to understand and explain, even for their developers, is a primary source of these unanticipated harms, making modern techniques and methods for manipulating large data sets seem sinister, even dangerous. When put in the hands of authoritarian governments, these algorithms have enabled suppression of political dissent and persecution of minorities. To prevent these harms, data scientists everywhere must come to understand how the algorithms that they build and deploy may harm certain groups or be unfair. Responsible Data Science delivers a comprehensive, practical treatment of how to implement data science solutions in an even-handed and ethical manner that minimizes the risk of undue harm to vulnerable members of society. Both data science practitioners and managers of analytics teams will learn how to: Improve model transparency, even for black box modelsDiagnose bias and unfairness within models using multiple metricsAudit projects to ensure fairness and minimize the possibility of unintended harm Perfect for data science practitioners, Responsible Data Science will also earn a spot on the bookshelves of technically inclined managers, software developers, and statisticians.
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Librería: moluna, Greven, , Alemaniamoluna
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 34,40
Envío por EUR 48,99Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New. GRANT FLEMING is a Data Scientist at Elder Research Inc. His professional focus is on machine learning for social science applications, model interpretability, civic technology, and building software tools for reproducible data science.PETER BRUCE is the Se.
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Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 28,43
Envío por EUR 75,35Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Paperback. Condición: New. Explore the most serious prevalent ethical issues in data science with this insightful new resource The increasing popularity of data science has resulted in numerous well-publicized cases of bias, injustice, and discrimination. The widespread deployment of "Black box" algorithms that are difficult or…impossible to understand and explain, even for their developers, is a primary source of these unanticipated harms, making modern techniques and methods for manipulating large data sets seem sinister, even dangerous. When put in the hands of authoritarian governments, these algorithms have enabled suppression of political dissent and persecution of minorities. To prevent these harms, data scientists everywhere must come to understand how the algorithms that they build and deploy may harm certain groups or be unfair. Responsible Data Science delivers a comprehensive, practical treatment of how to implement data science solutions in an even-handed and ethical manner that minimizes the risk of undue harm to vulnerable members of society. Both data science practitioners and managers of analytics teams will learn how to: Improve model transparency, even for black box modelsDiagnose bias and unfairness within models using multiple metricsAudit projects to ensure fairness and minimize the possibility of unintended harm Perfect for data science practitioners, Responsible Data Science will also earn a spot on the bookshelves of technically inclined managers, software developers, and statisticians.
