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Published by Information Science Reference, 2018
ISBN 10: 1522537961 ISBN 13: 9781522537960
Language: English
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Published by Information Science Reference, 2018
ISBN 10: 1522537961 ISBN 13: 9781522537960
Language: English
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Published by Information Science Reference, 2018
ISBN 10: 1522537961 ISBN 13: 9781522537960
Language: English
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Published by Information Science Reference, 2018
ISBN 10: 1522537961 ISBN 13: 9781522537960
Language: English
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Published by Information Science Reference, 2018
ISBN 10: 1522537961 ISBN 13: 9781522537960
Language: English
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Published by Information Science Reference, 2018
ISBN 10: 1522537961 ISBN 13: 9781522537960
Language: English
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Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032745975 ISBN 13: 9781032745978
Language: English
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Published by Information Science Reference, 2018
ISBN 10: 1522537961 ISBN 13: 9781522537960
Language: English
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Published by LAP LAMBERT Academic Publishing, 2015
ISBN 10: 3659795690 ISBN 13: 9783659795695
Language: English
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Balasubramanian KrishnasamyDr. K. Balasubramanian graduated from Madurai Kamaraj University and post graduated from Bharathidasan University, Trichy, India. He completed Ph.D. at Gandhigram Rural Institute-Deemed University, Gandhigr.
Published by Taylor & Francis Ltd, London, 2024
ISBN 10: 1032745975 ISBN 13: 9781032745978
Language: English
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Hardcover. Condition: new. Hardcover. The text comprehensively discusses the representation of visual data and design principles of interactive and dynamic dashboards. It further covers the theoretical concept of inference and machine learning algorithms for making the concepts clear to the reader. The book illustrates important topics such as data testing a parametric hypothesis, data testing a non-parametric hypothesis, exploratory data analysis, outlier detection and interpretation.This book: Covers various data analysis tools such as KNIME, RapidMiner, Rstudio, Grafana, and Redash Discusses the theoretical concept of inference and machine learning algorithms for designing dynamic dashboards Presents statistical modelling techniques with an emphasis on pattern mining, and pattern relationships Explains the problem of efficient retrieval of similar time series in large databases to enrich the knowledge of the readers to effectively handle various real-time datasets Illustrates dimensionality reduction techniques such as principal component analysis, linear discriminant analysis, singular value decomposition, and piecewise vector quantized approximationIt is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology. The text comprehensively discusses the representation of visual data and design principles of interactive and dynamic dashboards. It further covers the theoretical concept of inference and machine learning algorithms for making the concepts clear to the reader. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Published by Information Science Reference, 2017
ISBN 10: 1522537961 ISBN 13: 9781522537960
Language: English
Seller: moluna, Greven, Germany
Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Explores methods and strategies related to multimedia information retrieval systems. Featuring coverage on a broad range of topics including content-based image retrieval, text-based image retrieval, fuzzy object shape features, encoding, and indexing, this.
Published by Taylor & Francis Ltd, London, 2024
ISBN 10: 1032745975 ISBN 13: 9781032745978
Language: English
Seller: CitiRetail, Stevenage, United Kingdom
Hardcover. Condition: new. Hardcover. The text comprehensively discusses the representation of visual data and design principles of interactive and dynamic dashboards. It further covers the theoretical concept of inference and machine learning algorithms for making the concepts clear to the reader. The book illustrates important topics such as data testing a parametric hypothesis, data testing a non-parametric hypothesis, exploratory data analysis, outlier detection and interpretation.This book: Covers various data analysis tools such as KNIME, RapidMiner, Rstudio, Grafana, and Redash Discusses the theoretical concept of inference and machine learning algorithms for designing dynamic dashboards Presents statistical modelling techniques with an emphasis on pattern mining, and pattern relationships Explains the problem of efficient retrieval of similar time series in large databases to enrich the knowledge of the readers to effectively handle various real-time datasets Illustrates dimensionality reduction techniques such as principal component analysis, linear discriminant analysis, singular value decomposition, and piecewise vector quantized approximationIt is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology. The text comprehensively discusses the representation of visual data and design principles of interactive and dynamic dashboards. It further covers the theoretical concept of inference and machine learning algorithms for making the concepts clear to the reader. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Published by Taylor & Francis Ltd, London, 2024
ISBN 10: 1032745975 ISBN 13: 9781032745978
Language: English
Seller: AussieBookSeller, Truganina, VIC, Australia
Hardcover. Condition: new. Hardcover. The text comprehensively discusses the representation of visual data and design principles of interactive and dynamic dashboards. It further covers the theoretical concept of inference and machine learning algorithms for making the concepts clear to the reader. The book illustrates important topics such as data testing a parametric hypothesis, data testing a non-parametric hypothesis, exploratory data analysis, outlier detection and interpretation.This book: Covers various data analysis tools such as KNIME, RapidMiner, Rstudio, Grafana, and Redash Discusses the theoretical concept of inference and machine learning algorithms for designing dynamic dashboards Presents statistical modelling techniques with an emphasis on pattern mining, and pattern relationships Explains the problem of efficient retrieval of similar time series in large databases to enrich the knowledge of the readers to effectively handle various real-time datasets Illustrates dimensionality reduction techniques such as principal component analysis, linear discriminant analysis, singular value decomposition, and piecewise vector quantized approximationIt is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology. The text comprehensively discusses the representation of visual data and design principles of interactive and dynamic dashboards. It further covers the theoretical concept of inference and machine learning algorithms for making the concepts clear to the reader. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Buch. Condition: Neu. Interactive and Dynamic Dashboard | Design Principles | A. Vadivel (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2024 | CRC Press | EAN 9781032745978 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The text comprehensively discusses the representation of visual data and design principles of interactive and dynamic dashboards. It further covers the theoretical concept of inference and machine learning algorithms for making the concepts clear to the reader.