Data Science Foundations

Geometry and Topology of Complex Hierarchic Systems and Big Data Analytics

Nonfiction, Science & Nature, Mathematics, Applied, Statistics, Computers, Database Management
Cover of the book Data Science Foundations by Fionn Murtagh, CRC Press
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Author: Fionn Murtagh ISBN: 9781315350493
Publisher: CRC Press Publication: September 22, 2017
Imprint: Chapman and Hall/CRC Language: English
Author: Fionn Murtagh
ISBN: 9781315350493
Publisher: CRC Press
Publication: September 22, 2017
Imprint: Chapman and Hall/CRC
Language: English

"Data Science Foundations is most welcome and, indeed, a piece of literature that the field is very much in need of…quite different from most data analytics texts which largely ignore foundational concepts and simply present a cookbook of methods…a very useful text and I would certainly use it in my teaching."
- Mark Girolami, Warwick University

Data Science encompasses the traditional disciplines of mathematics, statistics, data analysis, machine learning, and pattern recognition. This book is designed to provide a new framework for Data Science, based on a solid foundation in mathematics and computational science. It is written in an accessible style, for readers who are engaged with the subject but not necessarily experts in all aspects. It includes a wide range of case studies from diverse fields, and seeks to inspire and motivate the reader with respect to data, associated information, and derived knowledge.

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"Data Science Foundations is most welcome and, indeed, a piece of literature that the field is very much in need of…quite different from most data analytics texts which largely ignore foundational concepts and simply present a cookbook of methods…a very useful text and I would certainly use it in my teaching."
- Mark Girolami, Warwick University

Data Science encompasses the traditional disciplines of mathematics, statistics, data analysis, machine learning, and pattern recognition. This book is designed to provide a new framework for Data Science, based on a solid foundation in mathematics and computational science. It is written in an accessible style, for readers who are engaged with the subject but not necessarily experts in all aspects. It includes a wide range of case studies from diverse fields, and seeks to inspire and motivate the reader with respect to data, associated information, and derived knowledge.

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