How to Think about Data Science

1. Auflage 2022
ISBN: 978-1-032-36963-1
Verlag: Chapman and Hall/CRC

Buch, Englisch, 300 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 569 g

Reihe: Chapman & Hall/CRC Data Science Series

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.

Zielgruppe

Academic

Autoren/Hrsg.

Miranda-Saavedra, Diego

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Spiele-Programmierung, Rendering, Animation
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsvisualisierung

Inhaltsverzeichnis

A bird’s-eye view and the art of asking questions. Descriptive Analytics. Predictive Analytics. How are predictive models trained and evaluated? Are our algorithms racist, sexist and discriminating? Personal data, privacy and cybersecurity. What are the limits of Artificial Intelligence?

Über Autor(innen)

Diego Miranda Saavedra is a data scientist and a financial investor with a technical management and business background. His formal education includes a PhD (data analysis), an MSc in business analytics, and an MS in software engineering from the University of Oxford.

As part of a research career in data science, Diego has made seminal contributions and worked in renowned research institutes around the world. These include the Wellcome Trust Biocentre (Dundee, UK), the Cambridge Institute for Medical Research (Cambridge, UK) and the WPI Immunology Frontier Research Center (Osaka University, Japan) where he led the bioinformatics and genomics research laboratory. While at the University of Cambridge, Diego was also elected a fellow of Wolfson College.

Diego also loves teaching data science and is currently an adjunct professor at the Faculty of Economics of the University of Groningen and at the Universitat Oberta de Catalunya.