Data Science in Context: Foundations, Challenges, Opportunities

ISBN-13: 9781009272209 / Angielski / Twarda / 2022

New York) Wing Jeannette M. (Columbia University

Opis

Four leading experts convey the promise of data science and examine challenges in achieving its benefits and mitigating some harms.

Recenzje

'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

Spis treści

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.