Da: Books From California, Simi Valley, CA, U.S.A.
paperback. Condizione: Very Good. Cover and edges may have some wear.
Condizione: As New. Unread book in perfect condition.
Da: Devils in the Detail Ltd, Oxford, Regno Unito
EUR 14,29
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: Very Good. Picture Shown is For Illustration Purposes Only : CONDITION : VERY GOOD : PAPERBACK :light wear and scuff marks to cover, pages in nice condition, shipped from the UK.
Condizione: New.
Lingua: Inglese
Editore: National Academies Press, Washington, 2025
ISBN 10: 0309726662 ISBN 13: 9780309726665
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condizione: new. Paperback. Advances in artificial intelligence, and specifically in machine learning, are enabling new capabilities across nearly every sector of the economy. Many of these applications - such as automated vehicles, the power grid, or surgical robots - are safety critical: where malfunctions can result in harm to people, the environment, or property. While machine learning is already being deployed to enhance the capabilities of some physical systems, extending the rigorous practices of safety engineering to include machine learning components brings significant challenges.Machine Learning for Safety-Critical Applications explores ways to safely integrate machine learning into physical systems and presents research priorities for improving safety, testing, and evaluation. This report finds that designing machine learning algorithms in a way that aligns with safety engineering standards will require changes in research, training, and engineering practice - as well as a shift away from focusing on algorithmic performance in isolation. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
EUR 36,53
Quantità: 10 disponibili
Aggiungi al carrelloCondizione: New. 2025. paperback. . . . . .
Da: Revaluation Books, Exeter, Regno Unito
EUR 37,14
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 106 pages. 8.44x0.33x10.95 inches. In Stock.
Condizione: New. 2025. paperback. . . . . . Books ship from the US and Ireland.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 37,49
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 37,97
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: New.
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 37,98
Quantità: 1 disponibili
Aggiungi al carrelloPaperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.
Lingua: Inglese
Editore: National Academies Press, Washington, 2025
ISBN 10: 0309726662 ISBN 13: 9780309726665
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 42,55
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: new. Paperback. Advances in artificial intelligence, and specifically in machine learning, are enabling new capabilities across nearly every sector of the economy. Many of these applications - such as automated vehicles, the power grid, or surgical robots - are safety critical: where malfunctions can result in harm to people, the environment, or property. While machine learning is already being deployed to enhance the capabilities of some physical systems, extending the rigorous practices of safety engineering to include machine learning components brings significant challenges.Machine Learning for Safety-Critical Applications explores ways to safely integrate machine learning into physical systems and presents research priorities for improving safety, testing, and evaluation. This report finds that designing machine learning algorithms in a way that aligns with safety engineering standards will require changes in research, training, and engineering practice - as well as a shift away from focusing on algorithmic performance in isolation. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Lingua: Inglese
Editore: National Academies Press, Washington, 2025
ISBN 10: 0309726662 ISBN 13: 9780309726665
Da: CitiRetail, Stevenage, Regno Unito
EUR 38,69
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: new. Paperback. Advances in artificial intelligence, and specifically in machine learning, are enabling new capabilities across nearly every sector of the economy. Many of these applications - such as automated vehicles, the power grid, or surgical robots - are safety critical: where malfunctions can result in harm to people, the environment, or property. While machine learning is already being deployed to enhance the capabilities of some physical systems, extending the rigorous practices of safety engineering to include machine learning components brings significant challenges.Machine Learning for Safety-Critical Applications explores ways to safely integrate machine learning into physical systems and presents research priorities for improving safety, testing, and evaluation. This report finds that designing machine learning algorithms in a way that aligns with safety engineering standards will require changes in research, training, and engineering practice - as well as a shift away from focusing on algorithmic performance in isolation. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.