9783030455736 - guide to intelligent data science: how to intelligently make use of real data (texts in computer science) de borgelt, christian; höppner, frank; berthold, michael r. (20 resultados)
Guide to Intelligent Data Science: How to Intelligently Make Use of Real Data (Texts in Computer Science)
Berthold, Michael R.; Borgelt, Christian; Höppner, Frank; Klawonn, Frank; Silipo, Rosaria
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Guide to Intelligent Data Science: How to Intelligently Make Use of Real Data (Texts in Computer Science)
Berthold, Michael R.; Borgelt, Christian; Höppner, Frank; Klawonn, Frank; Silipo, Rosaria
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Guide to Intelligent Data Science : How to Intelligently Make Use of Real Data
Berthold, Michael R.; Borgelt, Christian; Höppner, Frank; Klawonn, Frank; Silipo, Rosaria
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Guide to Intelligent Data Science: How to Intelligently Make Use of Real Data (Texts in Computer Science)
Berthold, Michael R.; Borgelt, Christian; Höppner, Frank; Klawonn, Frank; Silipo, Rosaria
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Guide to Intelligent Data Science
Berthold, Michael R.; Borgelt, Christian; Höppner, Frank; Klawonn, Frank; Silipo, Rosaria
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Guide to Intelligent Data Science: How to Intelligently Make Use of Real Data (Texts in Computer Science)
Berthold, Michael R.; Borgelt, Christian; Höppner, Frank; Klawonn, Frank; Silipo, Rosaria
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Guide to Intelligent Data Science : How to Intelligently Make Use of Real Data
Berthold, Michael R.; Borgelt, Christian; Höppner, Frank; Klawonn, Frank; Silipo, Rosaria
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Guide to Intelligent Data Science : How to Intelligently Make Use of Real Data
Berthold, Michael R.; Borgelt, Christian; Höppner, Frank; Klawonn, Frank; Silipo, Rosaria
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Guide to Intelligent Data Science : How to Intelligently Make Use of Real Data
Berthold, Michael R.; Borgelt, Christian; Höppner, Frank; Klawonn, Frank; Silipo, Rosaria
Idioma: Inglés
Editorial: Springer, 2020
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Guide to Intelligent Data Science
Michael R. Berthold, Christian Borgelt, Frank Höppner, Frank Klawonn, Rosaria Silipo
Idioma: Inglés
Editorial: Springer Nature Switzerland AG, CH, 2020
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Hardback. Condición: New. Second Edition 2020. Making use of data is not anymore a niche project but central to almost every project. With access to massive compute resources and vast amounts of data, it seems at least in principle possible to solve any problem. However, successful data science projects result from the intellige…nt application of: human intuition in combination with computational power; sound background knowledge with computer-aided modelling; and critical reflection of the obtained insights and results.Substantially updating the previous edition, then entitled Guide to Intelligent Data Analysis, this core textbook continues to provide a hands-on instructional approach to many data science techniques, and explains how these are used to solve real world problems. The work balances the practical aspects of applying and using data science techniques with the theoretical and algorithmic underpinnings from mathematics and statistics. Major updates on techniques and subject coverage (including deep learning) are included.Topics and features: guides the reader through the process of data science, following the interdependent steps of project understanding, data understanding, data blending and transformation, modeling, as well as deployment and monitoring; includes numerous examples using the open source KNIME Analytics Platform, together with an introductory appendix; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; integrates illustrations and case-study-style examples to support pedagogical exposition; supplies further tools and information at an associated website.This practical and systematic textbook/reference is a "need-to-have" tool for graduate and advanced undergraduate students and essential reading for all professionals who face data science problems. Moreover, it is a "need to use, need to keep" resource following one's exploration of thesubject.
Guide to Intelligent Data Science: How to Intelligently Make Use of Real Data (Texts in Computer Science)
Berthold, Michael R., Borgelt, Christian, Höppner, Frank, Kl
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Guide to Intelligent Data Science: How to Intelligently Make Use of Real Data
Berthold, Michael R./ Borgelt, Christian/ Höppner, Frank/ Klawonn, Frank/ Silipo, Rosaria
Idioma: Inglés
Editorial: Springer-Nature New York Inc, 2020
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Hardcover. Condición: Brand New. 2nd edition. 420 pages. 9.25x6.00x1.00 inches. In Stock.
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Making use of data is not anymore a niche project but central to almost every project. With access to massive compute resources and vast amounts of data, it seems at least in principle possible to solve any problem. However, successful data science projec…ts result from the intelligent application of: human intuition in combination with computational power; sound background knowledge with computer-aided modelling; and critical reflection of the obtained insights and results.Substantially updating the previous edition, then entitledGuide to Intelligent Data Analysis, this core textbook continues to provide a hands-on instructional approach to many data science techniques, and explains how these are used to solve real world problems. The work balances the practical aspects of applying and using data science techniques with the theoretical and algorithmic underpinnings from mathematics and statistics. Major updates on techniques and subject coverage (including deep learning) are included.Topics and features: guides the reader through the process of data science, following the interdependent steps of project understanding, data understanding, data blending and transformation, modeling, as well as deployment and monitoring; includes numerous examples using the open source KNIME Analytics Platform, together with an introductory appendix; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; integrates illustrations and case-study-style examples to support pedagogical exposition; supplies further tools and information at an associated website.This practical and systematic textbook/reference is a 'need-to-have' tool for graduate and advanced undergraduate students and essential reading for all professionals who face data science problems. Moreover, it is a 'need to use, need to keep' resource following one's exploration of thesubject.
Guide to Intelligent Data Science
Michael R. Berthold, Christian Borgelt, Frank Höppner, Frank Klawonn, Rosaria Silipo
Idioma: Inglés
Editorial: Springer Nature Switzerland AG, CH, 2020
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Hardback. Condición: New. Second Edition 2020. Making use of data is not anymore a niche project but central to almost every project. With access to massive compute resources and vast amounts of data, it seems at least in principle possible to solve any problem. However, successful data science projects result from the intellige…nt application of: human intuition in combination with computational power; sound background knowledge with computer-aided modelling; and critical reflection of the obtained insights and results.Substantially updating the previous edition, then entitled Guide to Intelligent Data Analysis, this core textbook continues to provide a hands-on instructional approach to many data science techniques, and explains how these are used to solve real world problems. The work balances the practical aspects of applying and using data science techniques with the theoretical and algorithmic underpinnings from mathematics and statistics. Major updates on techniques and subject coverage (including deep learning) are included.Topics and features: guides the reader through the process of data science, following the interdependent steps of project understanding, data understanding, data blending and transformation, modeling, as well as deployment and monitoring; includes numerous examples using the open source KNIME Analytics Platform, together with an introductory appendix; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; integrates illustrations and case-study-style examples to support pedagogical exposition; supplies further tools and information at an associated website.This practical and systematic textbook/reference is a "need-to-have" tool for graduate and advanced undergraduate students and essential reading for all professionals who face data science problems. Moreover, it is a "need to use, need to keep" resource following one's exploration of thesubject.
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Making use of data is not anymore a niche project but central to almost every project. With access to massive compute resources and vast amounts of data, it seems at least in principle possible to solve any problem. However, successful dat…a science projects result from the intelligent application of: human intuition in combination with computational power; sound background knowledge with computer-aided modelling; and critical reflection of the obtained insights and results.Substantially updating the previous edition, then entitledGuide to Intelligent Data Analysis, this core textbook continues to provide a hands-on instructional approach to many data science techniques, and explains how these are used to solve real world problems. The work balances the practical aspects of applying and using data science techniques with the theoretical and algorithmic underpinnings from mathematics and statistics. Major updates on techniques and subject coverage (including deep learning) are included.Topics and features: guides the reader through the process of data science, following the interdependent steps of project understanding, data understanding, data blending and transformation, modeling, as well as deployment and monitoring; includes numerous examples using the open source KNIME Analytics Platform, together with an introductory appendix; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; integrates illustrations and case-study-style examples to support pedagogical exposition; supplies further tools and information at an associated website.This practical and systematic textbook/reference is a 'need-to-have' tool for graduate and advanced undergraduate students and essential reading for all professionals who face data science problems. Moreover, it is a 'need to use, need to keep' resource following one's exploration of the subject. 436 pp. Englisch.
Guide to Intelligent Data Science
Michael R. Berthold|Christian Borgelt|Frank Höppner|Frank Klawonn|Rosaria Silipo
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Editorial: Springer International Publishing, 2020
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Supplies a broad-range of perspectives on data science, providing readers with a comprehensive account of the fieldPresents a focus on practical aspects, in addition to a detailed description of the theoryEm…phasizes the common pitfalls that.
Idioma: Inglés
Editorial: Springer, Birkhäuser Aug 2020, 2020
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Making use of data is not anymore a niche project but central to almost every project. With access to massive compute resources and vast amounts of data, it seems at least in principle possible to solve any problem. However, successful data sc…ience projects result from the intelligent application of: human intuition in combination with computational power; sound background knowledge with computer-aided modelling; and critical reflection of the obtained insights and results.Substantially updating the previous edition, then entitled Guide to Intelligent Data Analysis, this core textbook continues to provide a hands-on instructional approach to many data science techniques, and explains how these are used to solve real world problems. The work balances the practical aspects of applying and using data science techniques with the theoretical and algorithmic underpinnings from mathematics and statistics. Major updates on techniques and subject coverage (including deep learning) are included.Topics and features: guides the reader through the process of data science, following the interdependent steps of project understanding, data understanding, data blending and transformation, modeling, as well as deployment and monitoring; includes numerous examples using the open source KNIME Analytics Platform, together with an introductory appendix; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; integrates illustrations and case-study-style examples to support pedagogical exposition; supplies further tools and information at an associated website.This practical and systematic textbook/reference is a 'need-to-have' tool for graduate and advanced undergraduate students and essential reading for all professionals who face data science problems. Moreover, it is a 'need to use, need to keep' resource following one's exploration of thesubject.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 436 pp. Englisch.
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Buch. Condición: Neu. Guide to Intelligent Data Science | How to Intelligently Make Use of Real Data | Michael R. Berthold (u. a.) | Buch | Texts in Computer Science | xiii | Englisch | 2020 | Springer | EAN 9783030455736 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]…hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
