Machine Learning Refined

Foundations, Algorithms, and Applications

Author: Jeremy Watt,Reza Borhani,Aggelos Katsaggelos

Publisher: Cambridge University Press

ISBN: 1108480721

Category: Computers

Page: 544

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An intuitive approach to machine learning covering key concepts, real-world applications, and practical Python coding exercises.
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Sharing Economy and Big Data Analytics

Author: Soraya Sedkaoui,Mounia Khelfaoui

Publisher: John Wiley & Sons

ISBN: 111969499X

Category: Mathematics

Page: 268

View: 3615

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The different facets of the sharing economy offer numerous opportunities for businesses ? particularly those that can be distinguished by their creative ideas and their ability to easily connect buyers and senders of goods and services via digital platforms. At the beginning of the growth of this economy, the advanced digital technologies generated billions of bytes of data that constitute what we call Big Data. This book underlines the facilitating role of Big Data analytics, explaining why and how data analysis algorithms can be integrated operationally, in order to extract value and to improve the practices of the sharing economy. It examines the reasons why these new techniques are necessary for businesses of this economy and proposes a series of useful applications that illustrate the use of data in the sharing ecosystem.
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Data Clustering

Algorithms and Applications

Author: Charu C. Aggarwal,Chandan K. Reddy

Publisher: CRC Press

ISBN: 1315360411

Category: Business & Economics

Page: 652

View: 5101

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Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains. The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabilistic clustering, grid-based clustering, spectral clustering, and nonnegative matrix factorization Domains, covering methods used for different domains of data, such as categorical data, text data, multimedia data, graph data, biological data, stream data, uncertain data, time series clustering, high-dimensional clustering, and big data Variations and Insights, discussing important variations of the clustering process, such as semisupervised clustering, interactive clustering, multiview clustering, cluster ensembles, and cluster validation In this book, top researchers from around the world explore the characteristics of clustering problems in a variety of application areas. They also explain how to glean detailed insight from the clustering process—including how to verify the quality of the underlying clusters—through supervision, human intervention, or the automated generation of alternative clusters.
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Anaphora Resolution

Algorithms, Resources, and Applications

Author: Massimo Poesio,Roland Stuckardt,Yannick Versley

Publisher: Springer

ISBN: 3662479095

Category: Computers

Page: 508

View: 7806

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This book lays out a path leading from the linguistic and cognitive basics, to classical rule-based and machine learning algorithms, to today’s state-of-the-art approaches, which use advanced empirically grounded techniques, automatic knowledge acquisition, and refined linguistic modeling to make a real difference in real-world applications. Anaphora and coreference resolution both refer to the process of linking textual phrases (and, consequently, the information attached to them) within as well as across sentence boundaries, and to the same discourse referent. The book offers an overview of recent research advances, focusing on practical, operational approaches and their applications. In part I (Background), it provides a general introduction, which succinctly summarizes the linguistic, cognitive, and computational foundations of anaphora processing and the key classical rule- and machine-learning-based anaphora resolution algorithms. Acknowledging the central importance of shared resources, part II (Resources) covers annotated corpora, formal evaluation, preprocessing technology, and off-the-shelf anaphora resolution systems. Part III (Algorithms) provides a thorough description of state-of-the-art anaphora resolution algorithms, covering enhanced machine learning methods as well as techniques for accomplishing important subtasks such as mention detection and acquisition of relevant knowledge. Part IV (Applications) deals with a selection of important anaphora and coreference resolution applications, discussing particular scenarios in diverse domains and distilling a best-practice model for systematically approaching new application cases. In the concluding part V (Outlook), based on a survey conducted among the contributing authors, the prospects of the research field of anaphora processing are discussed, and promising new areas of interdisciplinary cooperation and emerging application scenarios are identified. Given the book’s design, it can be used both as an accompanying text for advanced lectures in computational linguistics, natural language engineering, and computer science, and as a reference work for research and independent study. It addresses an audience that includes academic researchers, university lecturers, postgraduate students, advanced undergraduate students, industrial researchers, and software engineers.
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Data Mining Algorithms

Explained Using R

Author: Pawel Cichosz

Publisher: John Wiley & Sons

ISBN: 1118950801

Category: Mathematics

Page: 720

View: 3152

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Data Mining Algorithms is a practical, technically-oriented guide to data mining algorithms that covers the most important algorithms for building classification, regression, and clustering models, as well as techniques used for attribute selection and transformation, model quality evaluation, and creating model ensembles. The author presents many of the important topics and methodologies widely used in data mining, whilst demonstrating the internal operation and usage of data mining algorithms using examples in R.
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Machine Learning

Proceedings of the Nineteenth International Conference (ICML 2002) : University of New South Wales, Sydney, Australia, July 8-12, 2002

Author: Claude Sammut,Achim Hoffmann

Publisher: Morgan Kaufmann

ISBN: 9781558608733

Category: Computers

Page: 706

View: 1738

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Proceedings of the annual International Conferences on Machine Learning, 1988-present. Current volume: ICML 2002: 19th International Conference on Machine Learning. Submissions are expected that describe empirical, theoretical, and cognitive-modeling research in all areas of machine learning. Submissions that present algorithms for novel learning tasks, interdisciplinary research involving machine learning, or innovative applications of machine learning techniques to challenging, real-world problems are especially encouraged.
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Machine learning

proceedings of the Eighth International Workshop (ML91)

Author: Lawrence Birnbaum,Gregg Collins

Publisher: Morgan Kaufmann

ISBN: 9781558602007

Category: Computers

Page: 661

View: 2889

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Encyclopedia of Library and Information Science: Volume 1 - Abbreviations

Accountability to Associcao Brasileira De Escolas De Biblioteconomia E Documentacao

Author: Allen Kent,Harold Lancour

Publisher: CRC Press

ISBN: 9780824720018

Category: Language Arts & Disciplines

Page: 688

View: 7838

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"The Encyclopedia of Library and Information Science provides an outstanding resource in 33 published volumes with 2 helpful indexes. This thorough reference set--written by 1300 eminent, international experts--offers librarians, information/computer scientists, bibliographers, documentalists, systems analysts, and students, convenient access to the techniques and tools of both library and information science. Impeccably researched, cross referenced, alphabetized by subject, and generously illustrated, the Encyclopedia of Library and Information Science integrates the essential theoretical and practical information accumulating in this rapidly growing field."
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