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Author: Marshall McLuhan
Publisher: Createspace Independent Publishing Platform
ISBN: 9781537430058
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Pages : 396
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When first published, Marshall McLuhan's Understanding Media made history with its radical view of the effects of electronic communications upon man and life in the twentieth century.
Author: William Frederick Doolittle
Publisher: Legare Street Press
ISBN: 9781016855594
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Pages : 0
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This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work is in the "public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
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Pages : 414
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Author: Dwight Loomis
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Category : Connecticut
Languages : en
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Author: Ellen Douglas Larned
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Category : Windham County (Conn.)
Languages : en
Pages : 618
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Author: Avrim Blum
Publisher: Cambridge University Press
ISBN: 1108617360
Category : Computers
Languages : en
Pages : 433
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This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.
Author: William Hand Browne
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Languages : en
Pages : 442
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Includes the proceedings of the Society.
Author: Charles Burr Todd
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Category : Iowa
Languages : en
Pages : 900
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