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Ajouter au panierhardcover. Etat : Very Good. Learning Systems: From Theory to Practice: 756 (Studies in Computational Intelligence, 756) This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .
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Ajouter au panierXII, 301 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Studies in Computational Intelligence. Volume 756. Sprache: Englisch.
Edité par Springer International Publishing AG, Cham, 2024
ISBN 10 : 3031700074 ISBN 13 : 9783031700071
Langue: anglais
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Ajouter au panierPaperback. Etat : new. Paperback. This book is a self-contained introduction to engineering and testing machine learning (ML) systems. It systematically discusses and teaches the art of crafting and developing software systems that include and surround machine learning models. Crafting ML based systems that are business-grade is highly challenging, as it requires statistical control throughout the complete system development life cycle. To this end, the book introduces an experiment first approach, stressing the need to define statistical experiments from the beginning of the development life cycle and presenting methods for careful quantification of business requirements and identification of key factors that impact business requirements. Applying these methods reduces the risk of failure of an ML development project and of the resultant, deployed ML system. The presentation is complemented by numerous best practices, case studies and practical as well as theoretical exercises and their solutions, designed to facilitate understanding of the ideas, concepts and methods introduced.The goal of this book is to empower scientists, engineers, and software developers with the knowledge and skills necessary to create robust and reliable ML software. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Edité par Lanzhou University Press Pub. Date :2009-03, 2000
ISBN 10 : 7311031788 ISBN 13 : 9787311031787
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Ajouter au panierpaperback. Etat : New. Paperback. Pub Date: 2009 Pages: 298 in Publisher: Lanzhou University Press' ordinary institutions of higher learning of economics and management planning materials. management information systems: Theory and Practice (2nd Edition) is divided into two parts. the first part of from the first nine chapters. the core theoretical knowledge of management information systems; second part of Chapter 10 and Chapter 11. belongs to the practice of teaching content. Contents: Chapter 1 Information Syste.
Edité par Springer-Nature New York Inc, 2024
ISBN 10 : 3031700074 ISBN 13 : 9783031700071
Langue: anglais
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Ajouter au panierPaperback. Etat : Brand New. 194 pages. 9.44x6.61x9.45 inches. In Stock.
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Ajouter au panierBrand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
Edité par Springer Nature Switzerland, Springer Nature Switzerland Okt 2024, 2024
ISBN 10 : 3031700074 ISBN 13 : 9783031700071
Langue: anglais
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Ajouter au panierTaschenbuch. Etat : Neu. Neuware -This book is a self-contained introduction to engineering and testing machine learning (ML) systems. It systematically discusses and teaches the art of crafting and developing software systems that include and surround machine learning models. Crafting ML based systems that are business-grade is highly challenging, as it requires statistical control throughout the complete system development life cycle. To this end, the book introduces an ¿experiment first¿ approach, stressing the need to define statistical experiments from the beginning of the development life cycle and presenting methods for careful quantification of business requirements and identification of key factors that impact business requirements. Applying these methods reduces the risk of failure of an ML development project and of the resultant, deployed ML system. The presentation is complemented by numerous best practices, case studies and practical as well as theoretical exercises and their solutions, designed to facilitate understanding of the ideas, concepts and methods introduced.The goal of this book is to empower scientists, engineers, and software developers with the knowledge and skills necessary to create robust and reliable ML software.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 196 pp. Englisch.
Edité par Springer Nature Switzerland, Springer Nature Switzerland, 2024
ISBN 10 : 3031700074 ISBN 13 : 9783031700071
Langue: anglais
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Ajouter au panierTaschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a self-contained introduction to engineering and testing machine learning (ML) systems. It systematically discusses and teaches the art of crafting and developing software systems that include and surround machine learning models. Crafting ML based systems that are business-grade is highly challenging, as it requires statistical control throughout the complete system development life cycle. To this end, the book introduces an 'experiment first' approach, stressing the need to define statistical experiments from the beginning of the development life cycle and presenting methods for careful quantification of business requirements and identification of key factors that impact business requirements. Applying these methods reduces the risk of failure of an ML development project and of the resultant, deployed ML system. The presentation is complemented by numerous best practices, case studies and practical as well as theoretical exercises and their solutions, designed to facilitate understanding of the ideas, concepts and methods introduced.The goal of this book is to empower scientists, engineers, and software developers with the knowledge and skills necessary to create robust and reliable ML software.
Edité par Springer Nature Switzerland, 2024
ISBN 10 : 3031700074 ISBN 13 : 9783031700071
Langue: anglais
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Ajouter au panierTaschenbuch. Etat : Neu. Theory and Practice of Quality Assurance for Machine Learning Systems | An Experiment-Driven Approach | Samuel Ackerman (u. a.) | Taschenbuch | xii | Englisch | 2024 | Springer Nature Switzerland | EAN 9783031700071 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Ajouter au panierEtat : Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Library sticker on front cover. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,550grams, ISBN:9780470399835.
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Edité par Wiley-Blackwell 2010-04-28, 2010
ISBN 10 : 047039983X ISBN 13 : 9780470399835
Langue: anglais
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Ajouter au panierHardcover. Etat : New.
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Ajouter au panierEtat : As New. Unread book in perfect condition.
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Ajouter au panierEtat : New. 2024th edition NO-PA16APR2015-KAP.
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Ajouter au panierEtat : As New. Unread book in perfect condition.