A cutting edge graduate level book on the way the mathematical analytics of big data can add value and bring competitive advantage to consumer-facing industries.
A cutting edge graduate level book on the way the mathematical analytics of big data can add value and bring competitive advantage to consumer-facing industries.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Peter Grindrod researches a range of topics in analytics for customer-facing industries and in particular for the digital society. He is in an almost unique position of having experience within commercial settings as well as within academia. He is a former President of the Institute of Mathematics and its Applications, member of the EPSRC and Chair of the EPSRC's User Panel. He authored Patterns and Waves (OUP 1991, 2nd edn 1996) and has been awarded a CBE for his contribution to mathematics R&D. In 1998 he was co-founder and Technical Director of a start-up company, Numbercraft Limited, supplying analytics services and software to retailers and consumer goods manufacturers. He is a co-founder of Cignifi Inc, a Boston-based company that uses mobile phone records to provide behaviour based credit referencing for pre pay customers in emerging economies. He is a founder of Counting Lab Ltd, a UK-based start-up translating state of the art mathematics into prototype products and services.
Inhaltsangabe
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
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
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