Data Science in Context: Foundations, Challenges, Opportunities
Autor Alfred Z. Spector, Peter Norvig, Chris Wiggins, Jeannette M. Wingen Limba Engleză Hardback – 19 oct 2022
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Specificații
ISBN-13: 9781009272209
ISBN-10: 1009272209
Pagini: 335
Dimensiuni: 174 x 250 x 22 mm
Greutate: 0.7 kg
Editura: Cambridge University Press
Colecția Cambridge University Press
Locul publicării:New York, United States
ISBN-10: 1009272209
Pagini: 335
Dimensiuni: 174 x 250 x 22 mm
Greutate: 0.7 kg
Editura: Cambridge University Press
Colecția Cambridge University Press
Locul publicării:New York, United States
Cuprins
Introduction; Part I. Data Science: 1. Foundations of data science; 2. Data science is transdisciplinary; 3. A framework for ethical considerations; Recap of Part I – Data Science; Part II. Applying Data Science: 4. Data science applications: six examples; 5. The analysis rubric; 6. Applying the analysis rubric; 7. A principlist approach to ethical considerations; Recap of Part II – Transitioning from Examples and Learnings to Challenges; Part III. Challenges in Applying Data Science: 8. Tractable data; 9. Building and deploying models; 10. Dependability; 11. Understandability; 12. Setting the right objectives; 13. Toleration of failures; 14. Ethical, legal, and societal challenges; Recap of Part III – Challenges in Applying Data Science; Part IV. Addressing Concerns: 15. Societal concerns; 16. Education and intelligent discourse; 17. Regulation; 18. Research and development; 19. Quality and ethical governance; Recap of Part IV – Addressing Concerns: 20. Concluding thoughts; Appendix. Summary of recommendations from Part IV; About the authors; References; Index.
Recenzii
'This book provides an important view of the contextual landscape for data science: the context of related fields of statistics, visualization, optimization, and computer science; the context of a broad range of applications, together with an analysis rubric; the context of societal impacts from dependability, to understandability, to ethical and legal questions. These are critically important factors for any practitioner of data science to understand, and for others to be aware of in evaluating the use of data science.' Daniel Huttenlocher, Massachusetts Institute of Technology
'As data science becomes a crucial element in momentous decisions of war and peace, as well as commerce and innovation, it is vital that it rests on sound foundations. This book is an important step forward in that regard, illuminating the context in which data science is practiced. It is essential reading for both data scientists and decision makers.' James Arroyo, Ditchley Foundation
'Data science touches every aspect of our modern lives. This book digs into the practical, legal, and ethical challenges that result. It is the only book that's comprehensive in its consideration of the thorny issues arising from the broad application and unprecedented growth of data science. If you do data science, you should read this book.' Michael D. Smith, Harvard University
'This book will be essential reading for all data scientists and data teams. The self-contained text explains what students and practitioners need to know to use data science more effectively and ethically. It draws on the authors' years of experience and offers practical insights into data science that complement other books that focus on specific techniques. I'll be referencing and recommending this book for many years to come.' Ben Lorica, Gradient Flow
'As data science becomes a crucial element in momentous decisions of war and peace, as well as commerce and innovation, it is vital that it rests on sound foundations. This book is an important step forward in that regard, illuminating the context in which data science is practiced. It is essential reading for both data scientists and decision makers.' James Arroyo, Ditchley Foundation
'Data science touches every aspect of our modern lives. This book digs into the practical, legal, and ethical challenges that result. It is the only book that's comprehensive in its consideration of the thorny issues arising from the broad application and unprecedented growth of data science. If you do data science, you should read this book.' Michael D. Smith, Harvard University
'This book will be essential reading for all data scientists and data teams. The self-contained text explains what students and practitioners need to know to use data science more effectively and ethically. It draws on the authors' years of experience and offers practical insights into data science that complement other books that focus on specific techniques. I'll be referencing and recommending this book for many years to come.' Ben Lorica, Gradient Flow
Notă biografică
Descriere
Four leading experts convey the promise of data science and examine challenges in achieving its benefits and mitigating some harms.