Da: ThriftBooks-Dallas, Dallas, TX, U.S.A.
Paperback. Condizione: Very Good. No Jacket. Former library book; May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
paperback. Condizione: 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 Officially withdrawn from the library and stamped "no longer property of library," purchased at a charity even for the library system Otherwise, a clean text -- NO writing, NO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.
Lingua: Inglese
Editore: O'Reilly Media, Incorporated, 2021
ISBN 10: 1492075736 ISBN 13: 9781492075738
Da: Better World Books: West, Reno, NV, U.S.A.
Condizione: 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.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New.
Da: Lakeside Books, Benton Harbor, MI, U.S.A.
EUR 34,51
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: 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!
Da: BargainBookStores, Grand Rapids, MI, U.S.A.
Paperback or Softback. Condizione: New. Practical Fairness: Achieving Fair and Secure Data Models. Book.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition.
EUR 40,94
Quantità: Più di 20 disponibili
Aggiungi al carrelloPaperback. Condizione: 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.
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
EUR 37,73
Quantità: 1 disponibili
Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 37,72
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: New.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 43,26
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 45,43
Quantità: 1 disponibili
Aggiungi al carrelloPaperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.
Da: Revaluation Books, Exeter, Regno Unito
EUR 57,79
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 330 pages. 9.50x7.25x0.75 inches. In Stock.
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
EUR 62,49
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: New. 2020. Paperback. . . . . .
EUR 42,73
Quantità: Più di 20 disponibili
Aggiungi al carrelloPaperback. Condizione: 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.
Condizione: New. 2020. Paperback. . . . . . Books ship from the US and Ireland.
EUR 45,22
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: 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.
EUR 58,70
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: 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.