Hypothesis Generation and Interpretation: Design Principles and Patterns for Big Data Applications (Studies in Big Data, 139) - Couverture rigide
Synopsis
This book focuses in detail on data science and data analysis and emphasizes the importance of data engineering and data management in the design of big data applications. The author uses patterns discovered in a collection of big data applications to provide design principles for hypothesis generation, integrating big data processing and management, machine learning and data mining techniques.
The book proposes and explains innovative principles for interpreting hypotheses by integrating micro-explanations (those based on the explanation of analytical models and individual decisions within them) with macro-explanations (those based on applied processes and model generation). Practical case studies are used to demonstrate how hypothesis-generation and -interpretation technologies work. These are based on “social infrastructure” applications like in-bound tourism, disaster management, lunar and planetary exploration, and treatment of infectious diseases.The novel methods and technologies proposed in Hypothesis Generation and Interpretation are supported by the incorporation of historical perspectives on science and an emphasis on the origin and development of the ideas behind their design principles and patterns.
Academic investigators and practitioners working on the further development and application of hypothesis generation and interpretation in big data computing, with backgrounds in data science and engineering, or the study of problem solving and scientific methods or who employ those ideas in fields like machine learning will find this book of considerable interest.Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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Hypothesis Generation and Interpretation : Design Principles and Patterns for Big Data Applications
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Hypothesis Generation and Interpretation (Hardcover)
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Hardcover. Etat : new. Hardcover. This book focuses in detail on data science and data analysis and emphasizes the importance of data engineering and data management in the design of big data applications. The author uses patterns discovered in a collection of big data applications to provide design principles for hypothesis generation, integrating big data processing and management, machine learning and data mining techniques.The book proposes and explains innovative principles for interpreting hypotheses by integrating micro-explanations (those based on the explanation of analytical models and individual decisions within them) with macro-explanations (those based on applied processes and model generation). Practical case studies are used to demonstrate how hypothesis-generation and -interpretation technologies work. These are based on social infrastructure applications like in-bound tourism, disaster management, lunar and planetary exploration, and treatment of infectious diseases.The novel methods and technologies proposed in Hypothesis Generation and Interpretation are supported by the incorporation of historical perspectives on science and an emphasis on the origin and development of the ideas behind their design principles and patterns. Academic investigators and practitioners working on the further development and application of hypothesis generation and interpretation in big data computing, with backgrounds in data science and engineering, or the study of problem solving and scientific methods or who employ those ideas in fields like machine learning will find this book of considerable interest. This book focuses in detail on data science and data analysis and emphasizes the importance of data engineering and data management in the design of big data applications. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9783031435393
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Hypothesis Generation and Interpretation: Design Principles and Patterns for Big Data Applications
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Hypothesis Generation and Interpretation
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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides an integrated perspective on why decisions are made and how the process is modeledPresentation of design patterns enables use in a wide variety of big-data applicationsMultiple practical use cases indicate the broad real-world sign. N° de réf. du vendeur 1027290410
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Hypothesis Generation and Interpretation
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Springer International Publishing Dez 2023, 2023
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book focuses in detail on data science and data analysis and emphasizes the importance of data engineering and data management in the design of big data applications. The author uses patterns discovered in a collection of big data applications to provide design principles for hypothesis generation, integrating big data processing and management, machine learning and data mining techniques.The book proposes and explains innovative principles for interpreting hypotheses by integrating micro-explanations (those based on the explanation of analytical models and individual decisions within them) with macro-explanations (those based on applied processes and model generation). Practical case studies are used to demonstrate how hypothesis-generation and -interpretation technologies work. These are based on 'social infrastructure' applications like in-bound tourism, disaster management, lunar and planetary exploration, and treatment of infectious diseases.The novel methods and technologies proposed inHypothesis Generation and Interpretation are supported by the incorporation of historical perspectives on science and an emphasis on the origin and development of the ideas behind their design principles and patterns. Academic investigators and practitioners working on the further development and application of hypothesis generation and interpretation in big data computing, with backgrounds in data science and engineering, or the study of problem solving and scientific methods or who employ those ideas in fields like machine learning will find this book of considerable interest. 384 pp. Englisch. N° de réf. du vendeur 9783031435393
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Hypothesis Generation and Interpretation : Design Principles and Patterns for Big Data Applications
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Hypothesis Generation and Interpretation
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Springer, Springer Feb 2024, 2024
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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book focuses in detail on data science and data analysis and emphasizes the importance of data engineering and data management in the design of big data applications. The author uses patterns discovered in a collection of big data applications to provide design principles for hypothesis generation, integrating big data processing and management, machine learning and data mining techniques.The book proposes and explains innovative principles for interpreting hypotheses by integrating micro-explanations (those based on the explanation of analytical models and individual decisions within them) with macro-explanations (those based on applied processes and model generation). Practical case studies are used to demonstrate how hypothesis-generation and -interpretation technologies work. These are based on 'social infrastructure' applications like in-bound tourism, disaster management, lunar and planetary exploration, and treatment of infectious diseases.The novel methods and technologies proposed in Hypothesis Generation and Interpretation are supported by the incorporation of historical perspectives on science and an emphasis on the origin and development of the ideas behind their design principles and patterns.Academic investigators and practitioners working on the further development and application of hypothesis generation and interpretation in big data computing, with backgrounds in data science and engineering, or the study of problem solving and scientific methods or who employ those ideas in fields like machine learning will find this book of considerable interest.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 384 pp. Englisch. N° de réf. du vendeur 9783031435393
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Hypothesis Generation and Interpretation : Design Principles and Patterns for Big Data Applications
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Springer International Publishing
ISBN 10 : 3031435397
ISBN 13 : 9783031435393
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses in detail on data science and data analysis and emphasizes the importance of data engineering and data management in the design of big data applications. The author uses patterns discovered in a collection of big data applications to provide design principles for hypothesis generation, integrating big data processing and management, machine learning and data mining techniques.The book proposes and explains innovative principles for interpreting hypotheses by integrating micro-explanations (those based on the explanation of analytical models and individual decisions within them) with macro-explanations (those based on applied processes and model generation). Practical case studies are used to demonstrate how hypothesis-generation and -interpretation technologies work. These are based on 'social infrastructure' applications like in-bound tourism, disaster management, lunar and planetary exploration, and treatment of infectious diseases.The novel methods and technologies proposed inHypothesis Generation and Interpretation are supported by the incorporation of historical perspectives on science and an emphasis on the origin and development of the ideas behind their design principles and patterns. Academic investigators and practitioners working on the further development and application of hypothesis generation and interpretation in big data computing, with backgrounds in data science and engineering, or the study of problem solving and scientific methods or who employ those ideas in fields like machine learning will find this book of considerable interest. N° de réf. du vendeur 9783031435393
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Hypothesis Generation and Interpretation
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ISBN 13 : 9783031435393
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Hypothesis Generation and Interpretation
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