The Resource Mathematical underpinnings of analytics : theory and applications, Peter Grindrod, CBE, Mathematical Institute, University of Oxford
Mathematical underpinnings of analytics : theory and applications, Peter Grindrod, CBE, Mathematical Institute, University of Oxford
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The item Mathematical underpinnings of analytics : theory and applications, Peter Grindrod, CBE, Mathematical Institute, University of Oxford represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in European University Institute.This item is available to borrow from 1 library branch.
Resource Information
The item Mathematical underpinnings of analytics : theory and applications, Peter Grindrod, CBE, Mathematical Institute, University of Oxford represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in European University Institute.
This item is available to borrow from 1 library branch.
 Summary
 Analytics is the application of mathematical and statistical concepts to large data sets so as to distil insights that offer the owner some options for action and competitive advantage or value. This makes it the most desirable and valuable part of big data science. Driven by the increased data capture from digital platforms, commercial fields are becoming data rich and analytics is growing in many sectors. This book presents analytics within a framework of mathematical theory and concepts building upon firm theory and foundations of probability theory, graphs and networks, random matrices, linear algebra, optimization, forecasting, discrete dynamical systems, and more. Following on from the theoretical considerations, applications are given to data from commercially relevant interests: supermarket baskets; loyalty cards; mobile phone call records; smart meters; 'omic' data; sales promotions; social media; and microblogging. Each chapter tackles a topic in analytics: social networks and digital marketing; forecasting; clustering and segmentation; inverse problems; Markov models of behavioural changes; multiple hypothesis testing and decisionmaking; and so on. Chapters start with background mathematical theory explained with a strong narrative and then give way to practical considerations and then to exemplar applications. Exercises (and solutions), external data resources, and suggestions for project work are given. The book includes an appendix giving a crash course in Bayesian reasoning, for both ease and completeness.
 Language
 eng
 Edition
 First edition.
 Extent
 xiii, 261 pages
 Contents

 Introduction: The Underpinnings of Analytics 1: Similarity, Graphs and Networks, Random Matrices and SVD 2: Dynamically Evolving Networks 3: Structure and Responsiveness 4: Clustering and Unsupervised Classication 5: Multiple Hypothesis Testing Over Live Data 6: Adaptive Forecasting 7: Customer Journeys and Markov Chains Appendix: Uncertainty, Probability and Reasoning
 Isbn
 9780198725091
 Label
 Mathematical underpinnings of analytics : theory and applications
 Title
 Mathematical underpinnings of analytics
 Title remainder
 theory and applications
 Statement of responsibility
 Peter Grindrod, CBE, Mathematical Institute, University of Oxford
 Language
 eng
 Summary
 Analytics is the application of mathematical and statistical concepts to large data sets so as to distil insights that offer the owner some options for action and competitive advantage or value. This makes it the most desirable and valuable part of big data science. Driven by the increased data capture from digital platforms, commercial fields are becoming data rich and analytics is growing in many sectors. This book presents analytics within a framework of mathematical theory and concepts building upon firm theory and foundations of probability theory, graphs and networks, random matrices, linear algebra, optimization, forecasting, discrete dynamical systems, and more. Following on from the theoretical considerations, applications are given to data from commercially relevant interests: supermarket baskets; loyalty cards; mobile phone call records; smart meters; 'omic' data; sales promotions; social media; and microblogging. Each chapter tackles a topic in analytics: social networks and digital marketing; forecasting; clustering and segmentation; inverse problems; Markov models of behavioural changes; multiple hypothesis testing and decisionmaking; and so on. Chapters start with background mathematical theory explained with a strong narrative and then give way to practical considerations and then to exemplar applications. Exercises (and solutions), external data resources, and suggestions for project work are given. The book includes an appendix giving a crash course in Bayesian reasoning, for both ease and completeness.
 Assigning source
 Provided by Publisher
 Cataloging source
 YDXCP
 http://library.link/vocab/creatorName
 Grindrod, Peter
 Dewey number
 006.31
 Illustrations
 illustrations
 Index
 index present
 Literary form
 non fiction
 Nature of contents
 bibliography
 http://library.link/vocab/subjectName

 Data mining
 Mathematical analysis
 Big data
 Label
 Mathematical underpinnings of analytics : theory and applications, Peter Grindrod, CBE, Mathematical Institute, University of Oxford
 Bibliography note
 Includes bibliographical references (pages 251258) and index
 Carrier category
 volume
 Carrier category code

 nc
 Carrier MARC source
 rdacarrier.
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent.
 Contents
 Introduction: The Underpinnings of Analytics 1: Similarity, Graphs and Networks, Random Matrices and SVD 2: Dynamically Evolving Networks 3: Structure and Responsiveness 4: Clustering and Unsupervised Classication 5: Multiple Hypothesis Testing Over Live Data 6: Adaptive Forecasting 7: Customer Journeys and Markov Chains Appendix: Uncertainty, Probability and Reasoning
 Control code
 FIEb17785443
 Dimensions
 25 cm.
 Edition
 First edition.
 Extent
 xiii, 261 pages
 Isbn
 9780198725091
 Media category
 unmediated
 Media MARC source
 rdamedia.
 Media type code

 n
 System control number
 (OCoLC)892563228
 Label
 Mathematical underpinnings of analytics : theory and applications, Peter Grindrod, CBE, Mathematical Institute, University of Oxford
 Bibliography note
 Includes bibliographical references (pages 251258) and index
 Carrier category
 volume
 Carrier category code

 nc
 Carrier MARC source
 rdacarrier.
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent.
 Contents
 Introduction: The Underpinnings of Analytics 1: Similarity, Graphs and Networks, Random Matrices and SVD 2: Dynamically Evolving Networks 3: Structure and Responsiveness 4: Clustering and Unsupervised Classication 5: Multiple Hypothesis Testing Over Live Data 6: Adaptive Forecasting 7: Customer Journeys and Markov Chains Appendix: Uncertainty, Probability and Reasoning
 Control code
 FIEb17785443
 Dimensions
 25 cm.
 Edition
 First edition.
 Extent
 xiii, 261 pages
 Isbn
 9780198725091
 Media category
 unmediated
 Media MARC source
 rdamedia.
 Media type code

 n
 System control number
 (OCoLC)892563228
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