Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 1108427138 ISBN 13: 9781108427135
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Añadir al carritoPaperback. Condición: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 1108427138 ISBN 13: 9781108427135
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Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 1108427138 ISBN 13: 9781108427135
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Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 1108427138 ISBN 13: 9781108427135
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Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 1108427138 ISBN 13: 9781108427135
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Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 1108427138 ISBN 13: 9781108427135
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Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 1108427138 ISBN 13: 9781108427135
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Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 1108427138 ISBN 13: 9781108427135
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Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 1108427138 ISBN 13: 9781108427135
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Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 1108427138 ISBN 13: 9781108427135
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Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 1108427138 ISBN 13: 9781108427135
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Idioma: Inglés
Publicado por Cambridge University Press, 2021
ISBN 10: 1108427138 ISBN 13: 9781108427135
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Añadir al carritoCondición: New. 2021. Hardcover. . . . . .
Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 1108427138 ISBN 13: 9781108427135
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Idioma: Inglés
Publicado por Cambridge University Press, GB, 2021
ISBN 10: 1108427138 ISBN 13: 9781108427135
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Añadir al carritoHardback. Condición: New. Learn about the state-of-the-art at the interface between information theory and data science with this first unified treatment of the subject. Written by leading experts in a clear, tutorial style, and using consistent notation and definitions throughout, it shows how information-theoretic methods are being used in data acquisition, data representation, data analysis, and statistics and machine learning. Coverage is broad, with chapters on signal acquisition, data compression, compressive sensing, data communication, representation learning, emerging topics in statistics, and much more. Each chapter includes a topic overview, definition of the key problems, emerging and open problems, and an extensive reference list, allowing readers to develop in-depth knowledge and understanding. Providing a thorough survey of the current research area and cutting-edge trends, this is essential reading for graduate students and researchers working in information theory, signal processing, machine learning, and statistics.
Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 1108427138 ISBN 13: 9781108427135
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Añadir al carritoHardcover. Condición: Brand New. 538 pages. 9.50x6.75x1.25 inches. In Stock.
Idioma: Inglés
Publicado por Cambridge University Press, GB, 2021
ISBN 10: 1108427138 ISBN 13: 9781108427135
Librería: Rarewaves.com UK, London, Reino Unido
EUR 145,64
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Añadir al carritoHardback. Condición: New. Learn about the state-of-the-art at the interface between information theory and data science with this first unified treatment of the subject. Written by leading experts in a clear, tutorial style, and using consistent notation and definitions throughout, it shows how information-theoretic methods are being used in data acquisition, data representation, data analysis, and statistics and machine learning. Coverage is broad, with chapters on signal acquisition, data compression, compressive sensing, data communication, representation learning, emerging topics in statistics, and much more. Each chapter includes a topic overview, definition of the key problems, emerging and open problems, and an extensive reference list, allowing readers to develop in-depth knowledge and understanding. Providing a thorough survey of the current research area and cutting-edge trends, this is essential reading for graduate students and researchers working in information theory, signal processing, machine learning, and statistics.
Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 1108427138 ISBN 13: 9781108427135
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 175,08
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Learn about the state-of-the-art at the interface between information theory and data science with this first unified treatment of the subject. Written by leading experts in a clear, tutorial style, and using consistent notation and definitions throughout, it shows how information-theoretic methods are being used in data acquisition, data representation, data analysis, and statistics and machine learning. Coverage is broad, with chapters on signal acquisition, data compression, compressive sensing, data communication, representation learning, emerging topics in statistics, and much more. Each chapter includes a topic overview, definition of the key problems, emerging and open problems, and an extensive reference list, allowing readers to develop in-depth knowledge and understanding. Providing a thorough survey of the current research area and cutting-edge trends, this is essential reading for graduate students and researchers working in information theory, signal processing, machine learning, and statistics.
Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoHardcover. Condición: Brand New. 538 pages. 9.50x6.75x1.25 inches. In Stock. This item is printed on demand.
Idioma: Inglés
Publicado por Cambridge University Press, Cambridge, 2021
ISBN 10: 1108427138 ISBN 13: 9781108427135
Librería: CitiRetail, Stevenage, Reino Unido
EUR 124,74
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Añadir al carritoHardcover. Condición: new. Hardcover. Learn about the state-of-the-art at the interface between information theory and data science with this first unified treatment of the subject. Written by leading experts in a clear, tutorial style, and using consistent notation and definitions throughout, it shows how information-theoretic methods are being used in data acquisition, data representation, data analysis, and statistics and machine learning. Coverage is broad, with chapters on signal acquisition, data compression, compressive sensing, data communication, representation learning, emerging topics in statistics, and much more. Each chapter includes a topic overview, definition of the key problems, emerging and open problems, and an extensive reference list, allowing readers to develop in-depth knowledge and understanding. Providing a thorough survey of the current research area and cutting-edge trends, this is essential reading for graduate students and researchers working in information theory, signal processing, machine learning, and statistics. The first unified treatment of the interface between information theory and emerging topics in data science, written in a clear, tutorial style. Covering topics such as data acquisition, representation, analysis, and communication, it is ideal for graduate students and researchers in information theory, signal processing, and machine learning. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Idioma: Inglés
Publicado por Cambridge University Press, 2021
ISBN 10: 1108427138 ISBN 13: 9781108427135
Librería: moluna, Greven, Alemania
EUR 128,80
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The first unified treatment of the interface between information theory and emerging topics in data science, written in a clear, tutorial style. Covering topics such as data acquisition, representation, analysis, and communication, it is ideal for graduate .
Idioma: Inglés
Publicado por Cambridge University Press, 2021
ISBN 10: 1108427138 ISBN 13: 9781108427135
Librería: preigu, Osnabrück, Alemania
EUR 133,55
Cantidad disponible: 5 disponibles
Añadir al carritoBuch. Condición: Neu. Information-Theoretic Methods in Data Science | Miguel R. D. Rodrigues (u. a.) | Buch | Gebunden | Englisch | 2021 | Cambridge University Press | EAN 9781108427135 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.