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  • Cambridge, Massachusetts : The MIT Press  (4)
  • Upper Saddle River, NJ : Prentice Hall
  • Maschinelles Lernen  (3)
  • Ethik  (2)
  • Informationsgesellschaft  (2)
  • Computer Science  (7)
Datasource
Material
Language
Years
  • 1
    Book
    Book
    Cambridge, Massachusetts : The MIT Press
    ISBN: 9780262537018
    Language: English
    Pages: 237 Seiten
    Edition: First MIT Press paperback edition
    DDC: 303.4834
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    Keywords: Künstliche Intelligenz ; Beschränkung ; Fehler ; Technikbewertung ; Informationsgesellschaft ; Kritik
    Note: Literaturverzeichnis: Seiten 211-225
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  • 2
    Book
    Book
    Cambridge, Massachusetts : The MIT Press
    ISBN: 9780262535434
    Language: English
    Pages: xi, 264 Seiten , Diagramme , 18 cm
    Series Statement: The MIT Press essential knowledge series
    Parallel Title: Erscheint auch als Kelleher, John D., 1974 - Data science
    Parallel Title: Erscheint auch als Kelleher, John D., 1974 - Data science
    DDC: 005.7
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    Keywords: Big data ; Machine learning ; Data mining ; Quantitative research ; Big data ; Data mining ; Machine learning ; Quantitative research ; Einführung ; Data Science ; Big Data ; Maschinelles Lernen
    Abstract: The goal of data science is to improve decision making through the analysis of data. Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges. Einführung in das Gebiet der Datenwissenschaft.
    Note: Hier auch später erschienene, unveränderte Nachdrucke
    URL: Cover
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  • 3
    ISBN: 9780262037310
    Language: English
    Pages: 1 Online-Ressource (xiv, 265 Seiten)
    Parallel Title: Erscheint auch als Peters, Jonas, 1984 - Elements of causal inference
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    Keywords: Mobile & handheld device programming / Apps programming ; Machine learning ; Neural networks & fuzzy systems ; Causation ; Computer algorithms ; Inference ; Logic, Symbolic and mathematical ; Machine learning ; Kausalität ; Maschinelles Lernen ; Algorithmus ; Inferenzstatistik
    Abstract: A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning.The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem. The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts
    Note: English
    URL: Volltext  (OAPEN Library: download the publication)
    URL: Volltext  (OAPEN Library: description of the publication)
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  • 4
    ISBN: 9780262035613
    Language: English
    Pages: xxii, 775 Seiten , Illustrationen, Diagramme , 24 cm
    Series Statement: Adaptive computation and machine learning
    Parallel Title: Erscheint auch als Goodfellow, Ian, 1987 - Deep learning
    Parallel Title: Erscheint auch als Goodfellow, Ian, 1987 - Deep learning
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    Keywords: Machine learning ; Machine learning ; Machine learning ; Deep learning ; Maschinelles Lernen
    Note: Weitere Infos unter http://www.deeplearningbook.org/ , Literaturverzeichnis: Seiten 711-766 , Hier auch später erschienene, unveränderte Nachdrucke , Jahr in CIP [2017]
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  • 5
    Book
    Book
    Upper Saddle River, NJ : Prentice Hall
    ISBN: 0131451936
    Language: English
    Pages: XVIII, 286 S , Ill., graph. Darst , 28 cm
    Edition: 1. ed
    DDC: 303.4833
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    Keywords: Computers and civilization ; Human-computer interaction ; Informationstechnik ; Informationsgesellschaft
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  • 6
    Book
    Book
    Upper Saddle River, NJ : Prentice Hall
    ISBN: 0130082155
    Language: English
    Edition: 2. ed.
    Series Statement: An Alan R. Apt book
    DDC: 303.4834
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    Keywords: Einführung ; Datenverarbeitung ; Ethik ; Rechtsinformatik ; Datenverarbeitung ; Gesellschaft ; Datenverarbeitung ; Sozialer Wandel
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  • 7
    Book
    Book
    Upper Saddle River, NJ : Prentice Hall
    ISBN: 0134587790
    Language: English
    Pages: XVII, 382 S. , graph. Darst.
    Series Statement: An Alan R. Apt book
    DDC: 303.48/34 21
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    Keywords: Computers ; Ethische aspecten ; Informatica ; Sociale aspecten ; Ethik ; Gesellschaft ; Computers -- Social aspects ; Computers -- Moral and ethical aspects ; Rechtsinformatik ; Gesellschaft ; Ethik ; Datenverarbeitung ; Sozialer Wandel ; Einführung ; Einführung ; Einführung ; Datenverarbeitung ; Ethik ; Rechtsinformatik ; Datenverarbeitung ; Gesellschaft ; Datenverarbeitung ; Sozialer Wandel
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