How to think about data science / Diego Miranda-Saavedra.
By: Miranda-Saavedra, Diego [author.].
Publisher: Boca Raton : CRC Press, ©2023Edition: First edition.Description: 275 p.Content type: text Media type: unmediated Carrier type: volumeISBN: 9781032375687; 9781032369631.Subject(s): Statistics | Information visualization | Artificial intelligence | AlgorithmsGenre/Form: Print books.Summary: "This book is a timely and critical introduction for people who are 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 the 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"--| Current location | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|
| On Shelf | QA276.12 .M57 2023 (Browse shelf) | Available | AU00000000019885 |
Includes bibliographical references and index.
"This book is a timely and critical introduction for people who are 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 the 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"--