Data Science Foundations: Geometry and Topology of Complex Hierarchic Systems and Big Data Analytics (Chapman & Hall/CRC Computer Science & Data Analysis)
| Author | : | |
| Rating | : | 4.27 (622 Votes) |
| Asin | : | 1498763936 |
| Format Type | : | paperback |
| Number of Pages | : | 224 Pages |
| Publish Date | : | 2017-03-21 |
| Language | : | English |
DESCRIPTION:
He then worked for a dozen years on the Hubble Space Telescope, as a European Space Agency Senior Scientist. . Following many Professor of Computer Science positions, teaching and research, and senior management positions in Ireland, France, USA and UK, he is very happy now to be advancing data science as Professor of Data Science, and Director, Centre for Mathematics and Data Science,&nb
In this book, on the contrary, the approach which is discussed goes a step further. This book is quite technical in some parts and some mathematical background will help the readers to understand the details provided in some chapters. The book contains many illustrative examples but also theory. This book is also quite different from most data analytics texts which largely ignore foundational concepts and simply present a cookbook of methods…Geometry, topology, metric mapping, random projections, and applications to chemical analysis data challenge the reader out of the comfort zone of superficial data analytics methods. Many books can be found for th
This book is designed to provide a new framework for Data Science, based on a solid foundation in mathematics and computational science. 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.. It is written in an accessible style, for readers who are engaged with the subject but not necessarily experts in all aspects. "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