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Data Science for Social Good - Bog

Bag om Data Science for Social Good

This book is a collection of reflections by thought leaders at first-mover organizations in the exploding field of "Data Science for Social Good", meant as the application of knowledge from computer science, complex systems and computational social science to challenges such as humanitarian response, public health, sustainable development. The book provides both an overview of scientific approaches to social impact ΓÇô identifying a social need, targeting an intervention, measuring impact ΓÇô and the complementary perspective of funders and philanthropies that are pushing forward this new sector. This book will appeal to students and researchers in the rapidly growing field of data science for social impact, to data scientists at companies whose data could be used to generate more public value, and to decision makers at nonprofits, foundations, and agencies that are designing their own agenda around data.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9783030789848
  • Indbinding:
  • Paperback
  • Sideantal:
  • 99
  • Udgivet:
  • 14. Oktober 2021
  • Udgave:
  • 12021
  • Størrelse:
  • 154x234x10 mm.
  • Vægt:
  • 186 g.
  • 2-3 uger.
  • 19. Oktober 2024

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Prøv i 30 dage for 45 kr.
Herefter fra 79 kr./md. Ingen binding.

Beskrivelse af Data Science for Social Good

This book is a collection of reflections by thought leaders at first-mover organizations in the exploding field of "Data Science for Social Good", meant as the application of knowledge from computer science, complex systems and computational social science to challenges such as humanitarian response, public health, sustainable development. The book provides both an overview of scientific approaches to social impact ΓÇô identifying a social need, targeting an intervention, measuring impact ΓÇô and the complementary perspective of funders and philanthropies that are pushing forward this new sector.

This book will appeal to students and researchers in the rapidly growing field of data science for social impact, to data scientists at companies whose data could be used to generate more public value, and to decision makers at nonprofits, foundations, and agencies that are designing their own agenda around data.

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