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Displaying results 1 to 5 of 5.

  1. The trouble with big data
    how datafication displaces cultural practices
    Author: Edmond, Jennifer
    Published: 2021
    Publisher:  Bloomsbury Publishing, London

    Location:
    Universitätsbibliothek der RWTH Aachen
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    Location:
    Katholische Hochschule Nordrhein-Westfalen (katho), Hochschulbibliothek
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    Location:
    Universitäts- und Stadtbibliothek Köln, Hauptabteilung
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    Series: Bloomsbury Studies in Digital Cultures
    Subjects: Humanities / Research / Data processing; Digital humanities; Big data; Culture; Data analysis: general
    Scope: 1 online resource
    Notes:

    Includes bibliographical references and index

    Also issued in print: Bloomsbury Academic, 2021
  2. <<The>> trouble with big data
    how datafication displaces cultural practices
    Author: Edmond, Jennifer; Horsley, Nicola; Lehmann, Jörg; Priddy, Mike
    Published: 2023
    Publisher:  Bloomsbury Publishing, London

    Introduction -- Chapter 1: Data and language -- Chapter 2: Data and sensemaking -- Chapter 3: Data and invisibility -- Chapter 4: Big data and the abyss of aggregation -- Chapter 5: Data and power -- Conclusion. "This book is available as open access... more

     

    Introduction -- Chapter 1: Data and language -- Chapter 2: Data and sensemaking -- Chapter 3: Data and invisibility -- Chapter 4: Big data and the abyss of aggregation -- Chapter 5: Data and power -- Conclusion. "This book is available as open access through the Bloomsbury Open programme and is available on www.bloomsburycollections.com. It is funded by Trinity College Dublin, DARIAH-EU and the European Commission. This book explores the challenges society faces with big data, through the lens of culture rather than social, political or economic trends, as demonstrated in the words we use, the values that underpin our interactions, the biases and assumptions that drive us. Focusing on areas such as data and language, data and sensemaking, data and power, data and invisibility, and big data aggregation, it demonstrates that humanities research, focusing on cultural rather than social, political or economic frames of reference for viewing technology, resists mass datafication for a reason, and that those very reasons can be instructive for the critical observation of big data research and innovation."--

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Print
    ISBN: 9781350239661
    Series: Bloomsbury studies in digital cultures
    Subjects: Humanities; Culture; Digital humanities; Big data; Big data; Data analysis: general
    Scope: viii, 182 Seiten
  3. <<The>> trouble with big data
    how datafication displaces cultural practices
    Author: Edmond, Jennifer; Horsley, Nicola; Lehmann, Jörg; Priddy, Mike
    Published: 2022
    Publisher:  Bloomsbury Academic, London

    "This book is available as open access through the Bloomsbury Open programme and is available on www.bloomsburycollections.com. It is funded by Trinity College Dublin, DARIAH-EU and the European Commission. This book explores the challenges society... more

     

    "This book is available as open access through the Bloomsbury Open programme and is available on www.bloomsburycollections.com. It is funded by Trinity College Dublin, DARIAH-EU and the European Commission. This book explores the challenges society faces with big data, through the lens of culture rather than social, political or economic trends, as demonstrated in the words we use, the values that underpin our interactions, the biases and assumptions that drive us. Focusing on areas such as data and language, data and sensemaking, data and power, data and invisibility, and big data aggregation, it demonstrates that humanities research, focusing on cultural rather than social, political or economic frames of reference for viewing technology, resists mass datafication for a reason, and that those very reasons can be instructive for the critical observation of big data research and innovation."--

     
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    Content information
    Volltext (kostenfrei)
    Source: Union catalogues
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9781350239630; 9781350239647; 9781350239654
    Other identifier:
    Series: Bloomsbury studies in digital cultures
    Subjects: Humanities; Culture; Digital humanities; Big data; Big data; Data analysis: general
    Scope: 1 Online-Ressource (x, 182 Seiten)
    Notes:

    Online-Erscheinungsdatum laut Landingpage: 13 December 2021
  4. Text Analytics for Corpus Linguistics and Digital Humanities
    Simple R Scripts and Tools
    Author: Schneider, Gerold
    Published: 2024
    Publisher:  Bloomsbury Academic, London ; Bloomsbury Publishing (UK)

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    Location:
    Katholische Hochschule Nordrhein-Westfalen (katho), Hochschulbibliothek
    Inter-library loan:
    No inter-library loan

    Location:
    Universitäts- und Stadtbibliothek Köln, Hauptabteilung
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    No inter-library loan
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
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    Edition: 1st ed
    Series: Language, Data Science and Digital Humanities
    Subjects: Corpora (Linguistics); Digital humanities; R (Computer program language); Computational linguistics; Data analysis: general; linguistics
    Scope: 1 online resource (224 pages)
  5. Dive into Deep Learning
    Author: Zhang, Aston; Li, Mu; Lipton, Zachary C.; Smola, Alexander J.
    Published: 2023
    Publisher:  Cambridge University Press, Cambridge

    Deep learning has revolutionized pattern recognition, introducing tools that power a wide range of technologies in such diverse fields as computer vision, natural language processing, and automatic speech recognition. Applying deep learning requires... more

    Location:
    Sächsische Landesbibliothek - Staats- und Universitätsbibliothek Dresden
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    bestellt
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    Deep learning has revolutionized pattern recognition, introducing tools that power a wide range of technologies in such diverse fields as computer vision, natural language processing, and automatic speech recognition. Applying deep learning requires you to simultaneously understand how to cast a problem, the basic mathematics of modeling, the algorithms for fitting your models to data, and the engineering techniques to implement it all. This book is a comprehensive resource that makes deep learning approachable, while still providing sufficient technical depth to enable engineers, scientists, and students to use deep learning in their own work. No previous background in machine learning or deep learning is required-every concept is explained from scratch and the appendix provides a refresher on the mathematics needed. Runnable code is featured throughout, allowing you to develop your own intuition by putting key ideas into practice

     
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    Content information
    Cover (lizenzpflichtig)
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Print
    ISBN: 9781009389433
    Subjects: COM089000; COM094000; COMPUTERS / Database Management / Data Mining; COMPUTERS / Database Management / General; COMPUTERS / Information Theory; COMPUTERS / Natural Language Processing; Data Mining; Data analysis: general; Data capture & analysis; Data mining; Datenerfassung und -analyse; Datenwissenschaft und -analyse: allgemein; Information theory; Informationstheorie; LANGUAGE ARTS & DISCIPLINES / Library & Information Science; Machine learning; Maschinelles Lernen; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung
    Scope: 574 Seiten
    Notes:

    Installation; Notation; 1. Introduction; 2. Preliminaries; 3. Linear neural networks for regression; 4. Linear neural networks for classification; 5. Multilayer perceptrons; 6. Builders guide; 7. Convolutional neural networks; 8. Modern convolutional neural networks; 9. Recurrent neural networks; 10. Modern recurrent neural networks; 11. Attention mechanisms and transformers; Appendix. Tools for deep learning; Bibliography; Index.