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Publicado por Olten, Lizenzausg. mit Genehmigung des Walter-Vlgs., 1983
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Añadir al carritoOlten, Lizenzausg. mit Genehmigung des Walter-Vlgs. 1983. 283 S. OLwd. mit OUmschl. Zeugnisse mystischer Welterfahrung. Sprache : de.
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Añadir al carritoCondición: Sehr gut. Zustand: Sehr gut | Seiten: 372 | Sprache: Englisch | Produktart: Bücher | Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field.
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Añadir al carritoTaschenbuch. Condición: Neu. Meta-Learning in Computational Intelligence | Norbert Jankowski (u. a.) | Taschenbuch | Studies in Computational Intelligence | ix | Englisch | 2013 | Springer | EAN 9783642268588 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Idioma: Inglés
Publicado por Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2013
ISBN 10: 3642268587 ISBN 13: 9783642268588
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field.
Idioma: Inglés
Publicado por Springer Berlin Heidelberg, 2011
ISBN 10: 3642209793 ISBN 13: 9783642209796
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field.
Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoPaperback. Condición: Brand New. 2011 edition. 372 pages. 9.25x6.10x0.88 inches. In Stock.
Idioma: Inglés
Publicado por Springer-Verlag New York Inc, 2011
ISBN 10: 3642209793 ISBN 13: 9783642209796
Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoPaperback. Condición: Brand New. 2008 edition. 261 pages. German language. 8.27x5.75x0.55 inches. In Stock.
Publicado por Berlin,, 2017
Librería: Treptower Buecherkabinett Inh. Schultz Volha, Berlin, Alemania
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Añadir al carritoCondición: Gut. 4°. 240, 240 Seiten. Orig.-Leinwand im OU. Seltene Privatdokumentation, nicht im KVK. - Reich illustrierte Reise einer 11-köpfigen Gruppenreise (Personen aus Kunst, Kultur und Architektur) nach Persien. Jeder der Mitreisenden erzählt von den Erlebnissen eines bestimmten Tages mit entsprechendem Bildmaterial. Die Mitglieder der Reise waren Norbert Bisky, M. Esser, St. Koal, A. Wätjen, A. Cornelsen, S. Kluckow, A. Schmitz, P. Kahlfeldt, T. Rantur, C. Baumhöver und M. Adli. - Aus der aufgelösten Architektursammlung P. u. P. Kahlfeldt Berlin. Gä-II-1-53 Bei Bestellungen auf Rechnung bleibt Vorkasse vorbehalten. Bestellungen erfolgen ohne Gewähr und gelten erst nach Bestätigung der Verfügbarkeit. Wir bieten günstigere Versandvariante für Bücher bis 1000 gr. Bitte Anfragen. Payment in advance is reserved for orders on account. Orders are made without guarantee and are only valid after availability has been confirmed. The shipping costs to non-EU countries may vary depending on the weight. We also offer cheaper shipping options for books up to 1000g. Sprache: Deutsch Gewicht in Gramm: 2000.
Idioma: Alemán
Publicado por Leipzig Koehler & Amelang, 1968
Librería: Flügel & Sohn GmbH, Dresden, Alemania
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Añadir al carritoCondición: Gut. Goldprägung auf vorderem Einbanddeckel und Rücken, Illustrationen von Werner Klemke, 365 Seiten Schutzumschlag minimal bestossen, minimal beschmutzt und minimal gebräunt, Vor- und Nachsatz leicht gebräunt Sprache: Deutsch Gewicht in Gramm: 495 13x20cm Leineneinband mit Schutzumschlag.
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Idioma: Inglés
Publicado por Springer Berlin Heidelberg Aug 2013, 2013
ISBN 10: 3642268587 ISBN 13: 9783642268588
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 208,64
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field. 372 pp. Englisch.
Idioma: Inglés
Publicado por Springer Berlin Heidelberg, 2011
ISBN 10: 3642209793 ISBN 13: 9783642209796
Librería: moluna, Greven, Alemania
EUR 197,62
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Añadir al carritoGebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Recent research in Meta-learning in computational intelligence Presents new Developments and Trends in Computational Intelligence and Learning Written by leading experts in the fieldComputational Intelligence (CI) community has de.
Idioma: Inglés
Publicado por Springer Berlin Heidelberg, 2013
ISBN 10: 3642268587 ISBN 13: 9783642268588
Librería: moluna, Greven, Alemania
EUR 197,62
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Recent research in Meta-learning in computational intelligence Presents new Developments and Trends in Computational Intelligence and Learning Written by leading experts in the fieldComputational Intelligence (CI) community has de.
Idioma: Inglés
Publicado por Springer Berlin Heidelberg Jun 2011, 2011
ISBN 10: 3642209793 ISBN 13: 9783642209796
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 235,39
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field. 372 pp. Englisch.
Idioma: Inglés
Publicado por Springer, Springer Aug 2013, 2013
ISBN 10: 3642268587 ISBN 13: 9783642268588
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 235,39
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 372 pp. Englisch.
Idioma: Inglés
Publicado por Springer, Springer Jun 2011, 2011
ISBN 10: 3642209793 ISBN 13: 9783642209796
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 235,39
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open.Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process.This is where algorithms that learn how to learnl come to rescue.Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn.This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 372 pp. Englisch.
Librería: Majestic Books, Hounslow, Reino Unido
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Añadir al carritoCondición: New. Print on Demand pp. 372 1237 Illus. (76 Col.).
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Añadir al carritoCondición: New. PRINT ON DEMAND pp. 372.