ABSTRACT

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.

chapter Chapter 1|20 pages

A Bird's-Eye View and the Art of Asking Questions

chapter Chapter 2|34 pages

Descriptive Analytics

chapter Chapter 3|66 pages

Predictive Analytics

chapter Chapter 4|18 pages

How Are Predictive Models Trained and Evaluated?

chapter Chapter 5|30 pages

Are Our Algorithms Racist, Sexist and Discriminating?

chapter Chapter 6|30 pages

Personal Data, Privacy and Cybersecurity

chapter Chapter 7|30 pages

What Are the Limits of Artificial Intelligence?