Librería: Oblivion Books, Seattle, WA, Estados Unidos de America
EUR 12,26
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Añadir al carritopaperback. Condición: Good. Good reading copy of a PLEASE NOTE: Ex-Library edition with the usual stamps and stickers. Officially withdrawn from the library and stamped "no longer property of library," purchased at a charity even for the library system Otherwise, a clean text -- NO writing, NO highlighting to text. A useful reading copy. Oversized. Clean text -- NO writing, NO highlighting to text.ÂPLEASE NOTE: Domestic US media (standard) US orders ONLY. NO international orders.
Idioma: Inglés
Publicado por O'Reilly Media, Incorporated, 2021
ISBN 10: 1492075736 ISBN 13: 9781492075738
Librería: Better World Books: West, Reno, NV, Estados Unidos de America
EUR 27,00
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Añadir al carritoCondición: Very Good. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Librería: Lakeside Books, Benton Harbor, MI, Estados Unidos de America
EUR 33,99
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Añadir al carritoCondición: 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!
Idioma: Inglés
Publicado por O'Reilly Media 12/29/2020, 2020
ISBN 10: 1492075736 ISBN 13: 9781492075738
Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de America
EUR 38,40
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Añadir al carritoPaperback or Softback. Condición: New. Practical Fairness: Achieving Fair and Secure Data Models. Book.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 37,84
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EUR 40,32
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Añadir al carritoPaperback. Condición: New. Fairness is becoming a paramount consideration for data scientists. Mounting evidence indicates that the widespread deployment of machine learning and AI in business and government is reproducing the same biases we're trying to fight in the real world. But what does fairness mean when it comes to code? This practical book covers basic concerns related to data security and privacy to help data and AI professionals use code that's fair and free of bias.Many realistic best practices are emerging at all steps along the data pipeline today, from data selection and preprocessing to closed model audits. Author Aileen Nielsen guides you through technical, legal, and ethical aspects of making code fair and secure, while highlighting up-to-date academic research and ongoing legal developments related to fairness and algorithms.Identify potential bias and discrimination in data science modelsUse preventive measures to minimize bias when developing data modeling pipelinesUnderstand what data pipeline components implicate security and privacy concernsWrite data processing and modeling code that implements best practices for fairnessRecognize the complex interrelationships between fairness, privacy, and data security created by the use of machine learning modelsApply normative and legal concepts relevant to evaluating the fairness of machine learning models.
EUR 40,42
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
EUR 37,66
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 43,46
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 45,34
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Añadir al carritoPaperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.
Idioma: Inglés
Publicado por Oreilly & Associates Inc, 2020
ISBN 10: 1492075736 ISBN 13: 9781492075738
Librería: Revaluation Books, Exeter, Reino Unido
EUR 56,81
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Añadir al carritoPaperback. Condición: Brand New. 330 pages. 9.50x7.25x0.75 inches. In Stock.
Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
EUR 62,49
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Añadir al carritoCondición: New. 2020. Paperback. . . . . .
EUR 42,05
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Añadir al carritoPaperback. Condición: New. Fairness is becoming a paramount consideration for data scientists. Mounting evidence indicates that the widespread deployment of machine learning and AI in business and government is reproducing the same biases we're trying to fight in the real world. But what does fairness mean when it comes to code? This practical book covers basic concerns related to data security and privacy to help data and AI professionals use code that's fair and free of bias.Many realistic best practices are emerging at all steps along the data pipeline today, from data selection and preprocessing to closed model audits. Author Aileen Nielsen guides you through technical, legal, and ethical aspects of making code fair and secure, while highlighting up-to-date academic research and ongoing legal developments related to fairness and algorithms.Identify potential bias and discrimination in data science modelsUse preventive measures to minimize bias when developing data modeling pipelinesUnderstand what data pipeline components implicate security and privacy concernsWrite data processing and modeling code that implements best practices for fairnessRecognize the complex interrelationships between fairness, privacy, and data security created by the use of machine learning modelsApply normative and legal concepts relevant to evaluating the fairness of machine learning models.
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
EUR 78,04
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Añadir al carritoCondición: New. 2020. Paperback. . . . . . Books ship from the US and Ireland.
EUR 45,22
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Añadir al carritoCondición: New. Fairness is becoming a paramount consideration for data scientists. This practical book covers basic concerns related to data security and privacy to help data and AI professionals use code that s fair and free of bias.Über den Autorrnr.
Idioma: Inglés
Publicado por O'reilly Media Jan 2021, 2021
ISBN 10: 1492075736 ISBN 13: 9781492075738
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 58,70
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Neuware - 'Fairness is becoming a paramount consideration for data scientists. Mounting evidence indicates that the widespread deployment of machine learning and AI in business and government is reproducing the same biases we're trying to fight in the real world. But what does fairness mean when it comes to code This practical book covers basic concerns related to data security and privacy to help data and AI professionals use code that's fair and free of bias.' -- Back cover.