How to Think about Data Science
eBook - ePub

How to Think about Data Science

  1. 276 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

How to Think about Data Science

About this book

This book is a timely and critical introduction for those interested in what data science is (and isn't), and how it should be applied. The language is conversational and the content is accessible for readers without a quantitative or computational background; but, at the same time, it is also a practical overview of the field for the more technical readers. The overarching goal is to demystify the field and teach the reader how to develop an analytical mindset instead of following recipes. The book takes the scientist's approach of focusing on asking the right question at every step as this is the single most important factor contributing to the success of a data science project. Upon finishing this book, the reader should be asking more questions than I have answered. This book is, therefore, a practising scientist's approach to explaining data science through questions and examples.

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Yes, you can access How to Think about Data Science by Diego Miranda-Saavedra in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Science General. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover Page
  2. Half-Title Page
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Dedication Page
  7. Contents
  8. Foreword
  9. Preface
  10. Acknowledgements
  11. List of Figures
  12. List of Tables
  13. Chapter 1 ▪ A Bird's-Eye View and the Art of Asking Questions
  14. Chapter 2 ▪ Descriptive Analytics
  15. Chapter 3 ▪ Predictive Analytics
  16. Chapter 4 ▪ How Are Predictive Models Trained and Evaluated?
  17. Chapter 5 ▪ Are Our Algorithms Racist, Sexist and Discriminating?
  18. Chapter 6 ▪ Personal Data, Privacy and Cybersecurity
  19. Chapter 7 ▪ What Are the Limits of Artificial Intelligence?
  20. Appendix—Answers to Chapter Review Questions
  21. Bibliography
  22. Index