Verlag: Jones & Bartlett Publishers, 2009
ISBN 10: 0763776475 ISBN 13: 9780763776473
Sprache: Englisch
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Verlag: Jones & Bartlett Learning, LLC, 2007
ISBN 10: 076374137X ISBN 13: 9780763741372
Sprache: Englisch
Anbieter: Better World Books, Mishawaka, IN, USA
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Verlag: Jones & Bartlett Publishers, 2009
ISBN 10: 0763776475 ISBN 13: 9780763776473
Sprache: Englisch
Anbieter: ThriftBooks-Atlanta, AUSTELL, GA, USA
Paperback. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
Verlag: Jones & Bartlett Learning, LLC, 2007
ISBN 10: 076374137X ISBN 13: 9780763741372
Sprache: Englisch
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Verlag: Jones & Bartlett Learning, LLC, 2009
ISBN 10: 0763776475 ISBN 13: 9780763776473
Sprache: Englisch
Anbieter: Better World Books Ltd, Dunfermline, Vereinigtes Königreich
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Verlag: Springer-Verlag New York Inc, 2018
ISBN 10: 3319918508 ISBN 13: 9783319918501
Sprache: Englisch
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Verlag: Jones & Bartlett Publishers, Incorporated, 2008
ISBN 10: 076374137X ISBN 13: 9780763741372
Sprache: Englisch
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In den WarenkorbZustand: New. pp. xi + 326 Illus.
Verlag: Jones & Bartlett Learning, LLC, 2008
ISBN 10: 076374137X ISBN 13: 9780763741372
Sprache: Englisch
Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USA
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Verlag: Jones & Bartlett Publishers, 2009
ISBN 10: 0763776475 ISBN 13: 9780763776473
Sprache: Englisch
Anbieter: Lost Books, AUSTIN, TX, USA
Trade paperback. Trade paperback (US). 351 p. Contains: Illustrations, black & white, Tables, black & white, Diagrams, Figures. Audience: General/trade. Fair. Highlighting/underlining. heavy notes & highlighting on some pages. Some wear to cover.
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paperback. Zustand: Good. Book is slightly bending/warping. Otherwise book shows minimal/no wear. Pages are clean, text and pictures are intact and unmarred.
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
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In den WarenkorbPaperback. Zustand: Brand New. 213 pages. 9.26x6.11x0.46 inches. In Stock.
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Verlag: Springer Nature Switzerland, Springer International Publishing Mär 2024, 2024
ISBN 10: 3031537696 ISBN 13: 9783031537691
Sprache: Englisch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: Neu. Neuware -This open access book constitutes the revised selected papers of the First International Symposium on AI, Data and Digitalization, SAIDD 2023, held in Sogndal, Norway, during May 9¿10, 2023.The 13 full papers included in this volume were carefully reviewed and selected from 42 submissions. The papers deal with the impact of data and AI on the digital revolution and their contribution to solving societal challenges.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 216 pp. Englisch.
Verlag: Springer Nature Switzerland Mär 2024, 2024
ISBN 10: 3031537696 ISBN 13: 9783031537691
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This open access book constitutes the revised selected papers of the First International Symposium on AI, Data and Digitalization, SAIDD 2023, held in Sogndal, Norway, during May 9-10, 2023.The 13 full papers included in this volume were carefully reviewed and selected from 42 submissions. The papers deal with the impact of data and AI on the digital revolution and their contribution to solving societal challenges.
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In den WarenkorbPaperback. Zustand: Brand New. 96 pages. 9.25x6.10x0.20 inches. In Stock.
Verlag: Springer International Publishing, Springer Nature Switzerland Dez 2018, 2018
ISBN 10: 3319918508 ISBN 13: 9783319918501
Sprache: Englisch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: Neu. Neuware -The big data tsunami changes the perspective of industrial and academic research in how they address both foundational questions and practical applications. This calls for a paradigm shift in algorithms and the underlying mathematical techniques. There is a need to understand foundational strengths and address the state of the art challenges in big data that could lead to practical impact. The main goal of this book is to introduce algorithmic techniques for dealing with big data sets. Traditional algorithms work successfully when the input data fits well within memory. In many recent application situations, however, the size of the input data is too large to fit within memory.Models of Computation for Big Data, covers mathematical models for developing such algorithms, which has its roots in the study of big data that occur often in various applications. Most techniques discussed come from research in the last decade. The book will be structured as a sequence of algorithmic ideas, theoretical underpinning, and practical use of that algorithmic idea. Intended for both graduate students and advanced undergraduate students, there are no formal prerequisites, but the reader should be familiar with the fundamentals of algorithm design and analysis, discrete mathematics, probability and have general mathematical maturity.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 112 pp. Englisch.
Verlag: Springer International Publishing, Springer International Publishing, 2018
ISBN 10: 3319918508 ISBN 13: 9783319918501
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The big data tsunami changes the perspective of industrial and academic research in how they address both foundational questions and practical applications. This calls for a paradigm shift in algorithms andthe underlying mathematical techniques. There is a need to understand foundational strengths andaddress the state of the art challenges in big data that could lead to practical impact. The main goal of this book is to introduce algorithmic techniques for dealing with big data sets. Traditional algorithms work successfully when the input data fits well within memory. In many recent application situations, however, the size of the input data is too large to fit within memory.Models of Computation for Big Data, covers mathematical models for developing such algorithms, which has its roots in the study of big data that occur often in various applications. Most techniques discussed come from research in the last decade. The book will be structured as a sequence of algorithmic ideas, theoretical underpinning, and practical use of that algorithmic idea. Intended for both graduate students and advanced undergraduate students, there are no formal prerequisites, but the reader should be familiar with the fundamentals of algorithm design and analysis, discrete mathematics, probability and have general mathematical maturity.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 119,44
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In den WarenkorbPaperback. Zustand: Brand New. 341 pages. 9.75x7.00x1.00 inches. In Stock.
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In den WarenkorbZustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
Verlag: Jones & Bartlett Learning, LLC, 2007
ISBN 10: 076374137X ISBN 13: 9780763741372
Sprache: Englisch
Anbieter: Better World Books, Mishawaka, IN, USA
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Zustand: Very Good. 1st Edition. Former library book; may include library markings. Used book that is in excellent condition. May show signs of wear or have minor defects.
EUR 119,98
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In den WarenkorbPaperback. Zustand: Brand New. reprint edition. 542 pages. 9.25x6.00x1.25 inches. In Stock.
Taschenbuch. Zustand: Neu. Models of Computation for Big Data | Rajendra Akerkar | Taschenbuch | viii | Englisch | 2018 | Springer | EAN 9783319918501 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Verlag: Springer International Publishing, Springer Nature Switzerland Aug 2018, 2018
ISBN 10: 3319974351 ISBN 13: 9783319974354
Sprache: Englisch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: Neu. Neuware -This book offers a practical guide to artificial intelligence (AI) techniques that are used in business. The book does not focus on AI models and algorithms, but instead provides an overview of the most popular and frequently used models in business. This allows the book to easily explain AI paradigms and concepts for business students and executives. Artificial Intelligence for Business is divided into six chapters. Chapter 1 begins with a brief introduction to AI and describes its relationship with machine learning, data science and big data analytics. Chapter 2 presents core machine learning workflow and the most effective machine learning techniques. Chapter 3 deals with deep learning, a popular technique for developing AI applications. Chapter 4 introduces recommendation engines for business and covers how to use them to be more competitive. Chapter 5 features natural language processing (NLP) for sentiment analysis focused on emotions. With the help of sentiment analysis, businesses can understand their customers better to improve their experience, which will help the businesses change their market position. Chapter 6 states potential business prospects of AI and the benefits that companies can realize by implementing AI in their processes.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 96 pp. Englisch.
EUR 35,45
Anzahl: 1 verfügbar
In den WarenkorbZustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book offers a practical guide to artificial intelligence (AI) techniques that are used in business. The book does not focus on AI models and algorithms, but instead provides an overview of the most popular and frequently used models in business. This allows the book to easily explain AI paradigms and concepts for business students and executives. Artificial Intelligence for Business is divided into six chapters. Chapter 1 begins with a brief introduction to AI and describes its relationship with machine learning, data science and big data analytics. Chapter 2 presents core machine learning workflow and the most effective machine learning techniques. Chapter 3 deals with deep learning, a popular technique for developing AI applications. Chapter 4 introduces recommendation engines for business and covers how to use them to be more competitive. Chapter 5 features natural language processing (NLP) for sentiment analysis focused on emotions. With the help of sentiment analysis, businesses can understand their customers better to improve their experience, which will help the businesses change their market position. Chapter 6 states potential business prospects of AI and the benefits that companies can realize by implementing AI in their processes.