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Data Science in Societal Applications

Om Data Science in Societal Applications

The book provides an insight into the practical applications and theoretical foundation of data science. The book discusses new ways of embracing agile approaches to various facets of data science, including machine learning and artificial intelligence, data mining, data visualization, and communication. The book includes contributions from academia and industry experts detailing the shortfalls of current tools and techniques used and generating the blueprint of the new technologies. The topics covered in the book range from theoretical and foundational research, platforms, methods, applications, and tools in data science. The chapters in the book add a social, geographical, and temporal dimension to data science research. The papers included are application-oriented that prepare and use data in discovery research. This book will provide researchers and practitioners with a detailed snapshot of current progress in data science. Moreover, it will stimulate new study, research, and the development of new applications.

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  • Språk:
  • Engelsk
  • ISBN:
  • 9789811951565
  • Bindende:
  • Paperback
  • Sider:
  • 208
  • Utgitt:
  • 17. september 2023
  • Utgave:
  • 23001
  • Dimensjoner:
  • 155x11x235 mm.
  • Vekt:
  • 362 g.
  • BLACK NOVEMBER
  Gratis frakt
Leveringstid: Ukjent

Beskrivelse av Data Science in Societal Applications

The book provides an insight into the practical applications and theoretical foundation of data science. The book discusses new ways of embracing agile approaches to various facets of data science, including machine learning and artificial intelligence, data mining, data visualization, and communication. The book includes contributions from academia and industry experts detailing the shortfalls of current tools and techniques used and generating the blueprint of the new technologies. The topics covered in the book range from theoretical and foundational research, platforms, methods, applications, and tools in data science. The chapters in the book add a social, geographical, and temporal dimension to data science research. The papers included are application-oriented that prepare and use data in discovery research. This book will provide researchers and practitioners with a detailed snapshot of current progress in data science. Moreover, it will stimulate new study, research, and the development of new applications.

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