Data Science in Practice. This item is unavailable.
Language: English
Published by Springer Nature Switzerland, 2018
- Softcover
- New

Unavailable
Softcover
Condition: New
US$ 141.58
Item description from seller
Data Science in Practice | Vicenç Torra (u. a.) | Taschenbuch | viii | Englisch | 2018 | Springer Nature Switzerland | EAN 9783030073749 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Seller Inventory # 117343690
- Title
- Data Science in Practice
- Author
- Vicenç Torra (u. a.)
- Publisher
- Springer Nature Switzerland
- Publication year
- 2018
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3030073742
- ISBN 13
- 9783030073749
- Item weight
- 318 grams
- Dimensions
- 235 x 155 x 12 mm
- Series
- Book 40 of 95: Studies in Big Data
- Seller catalogs
- Bücher
This book approaches big data, artificial intelligence, machine learning, and business intelligence through the lens of Data Science. We have grown accustomed to seeing these terms mentioned time and time again in the mainstream media. However, our understanding of what they actually mean often remains limited. This book provides a general overview of the terms and approaches used broadly in data science, and provides detailed information on the underlying theories, models, and application scenarios. Divided into three main parts, it addresses what data science is; how and where it is used; and how it can be implemented using modern open source software. The book offers an essential guide to modern data science for all students, practitioners, developers and managers seeking a deeper understanding of how various aspects of data science work, and of how they can be employed to gain a competitive advantage.
"Synopsis" may belong to another edition of this title.
From the Back Cover
This book approaches big data, artificial intelligence, machine learning, and business intelligence through the lens of Data Science. We have grown accustomed to seeing these terms mentioned time and time again in the mainstream media. However, our understanding of what they actually mean often remains limited. This book provides a general overview of the terms and approaches used broadly in data science, and provides detailed information on the underlying theories, models, and application scenarios. Divided into three main parts, it addresses what data science is; how and where it is used; and how it can be implemented using modern open source software. The book offers an essential guide to modern data science for all students, practitioners, developers and managers seeking a deeper understanding of how various aspects of data science work, and of how they can be employed to gain a competitive advantage.
"About the title" may belong to another edition of this title.