Language: English
Published by Independently published, 2019
ISBN 10: 1698152310 ISBN 13: 9781698152318
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition.
Language: English
Published by Independently published, 2019
ISBN 10: 1698152310 ISBN 13: 9781698152318
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: New.
Language: English
Published by Independently published, 2019
ISBN 10: 1698152310 ISBN 13: 9781698152318
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: As New. Unread book in perfect condition.
Language: English
Published by Independently published, 2019
ISBN 10: 1698152310 ISBN 13: 9781698152318
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: New.
Language: English
Published by Independently published, 2019
ISBN 10: 1698152310 ISBN 13: 9781698152318
Seller: California Books, Miami, FL, U.S.A.
Condition: New. Print on Demand.
Seller: Ria Christie Collections, Uxbridge, United Kingdom
£ 134.60
Quantity: Over 20 available
Add to basketCondition: New. In.
Seller: California Books, Miami, FL, U.S.A.
Condition: New.
Seller: Buchpark, Trebbin, Germany
Condition: Hervorragend. Zustand: Hervorragend | Seiten: 480 | Sprache: Englisch | Produktart: Bücher | This book has two main goals: to define data science through the work of data scientists and their results, namely data products, while simultaneously providing the reader with relevant lessons learned from applied data science projects at the intersection of academia and industry. As such, it is not a replacement for a classical textbook (i.e., it does not elaborate on fundamentals of methods and principles described elsewhere), but systematically highlights the connection between theory, on the one hand, and its application in specific use cases, on the other. With these goals in mind, the book is divided into three parts: Part I pays tribute to the interdisciplinary nature of data science and provides a common understanding of data science terminology for readers with different backgrounds. These six chapters are geared towards drawing a consistent picture of data science and were predominantly written by the editors themselves. Part II then broadens the spectrum by presenting views and insights from diverse authors ¿ some from academia and some from industry, ranging from financial to health and from manufacturing to e-commerce. Each of these chapters describes a fundamental principle, method or tool in data science by analyzing specific use cases and drawing concrete conclusions from them. The case studies presented, and the methods and tools applied, represent the nuts and bolts of data science. Finally, Part III was again written from the perspective of the editors and summarizes the lessons learned that have been distilled from the case studies in Part II. The section can be viewed as a meta-study on data science across a broad range of domains, viewpoints and fields. Moreover, it provides answers to the question of what the mission-critical factors for success in different data science undertakings are. The book targets professionals as well as students of data science:first, practicing data scientists in industry and academia who want to broaden their scope and expand their knowledge by drawing on the authors¿ combined experience. Second, decision makers in businesses who face the challenge of creating or implementing a data-driven strategy and who want to learn from success stories spanning a range of industries. Third, students of data science who want to understand both the theoretical and practical aspects of data science, vetted by real-world case studies at the intersection of academia and industry.
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Condition: New.
Language: English
Published by Springer International Publishing, 2019
ISBN 10: 3030118207 ISBN 13: 9783030118204
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book has two main goals: to define data science through the work of data scientists and their results, namely data products, while simultaneously providing the reader with relevant lessons learned from applied data science projects at the intersection of academia and industry. As such, it is not a replacement for a classical textbook (i.e., it does not elaborate on fundamentals of methods and principles described elsewhere), but systematically highlights the connection between theory, on the one hand, and its application in specific use cases, on the other. With these goals in mind, the book is divided into three parts: Part I pays tribute to the interdisciplinary nature of data science and provides a common understanding of data science terminology for readers with different backgrounds. These six chapters are geared towards drawing a consistent picture of data science and were predominantly written by the editors themselves. Part II then broadens the spectrum by presenting views and insights from diverse authors - some from academia and some from industry,ranging from financial to health and from manufacturing toe-commerce.Each of these chapters describes a fundamental principle, method or tool in data scienceby analyzing specific use cases and drawing concrete conclusions from them. The casestudies presented, and the methods and tools applied, represent the nuts and bolts ofdata science. Finally, Part III was again written from the perspective of the editors andsummarizes the lessons learned that have been distilled from the case studies in Part II.The section can be viewed as a meta-study on data science across a broad range of domains,viewpoints and fields. Moreover, it provides answers to the question of what the mission-critical factors for success in different data science undertakings are.The book targets professionals as well as students of data science:first, practicing datascientists in industry and academia who want to broaden their scope and expand their knowledge by drawing on the authors' combined experience. Second, decision makers in businesses who face the challenge of creating or implementing a data-driven strategy and who want to learn from success stories spanning a range of industries. Third, studentsof data science who want to understand both the theoretical and practical aspects of datascience, vetted by real-world case studies at the intersection of academia and industry.
Seller: Mispah books, Redhill, SURRE, United Kingdom
Hardcover. Condition: New. New. book.
Language: English
Published by Springer-Verlag New York Inc, 2019
ISBN 10: 3030118207 ISBN 13: 9783030118204
Seller: Revaluation Books, Exeter, United Kingdom
Hardcover. Condition: Brand New. 465 pages. 9.25x6.25x1.25 inches. In Stock.
Condition: New.
Language: English
Published by Independently Published, 2019
ISBN 10: 1698152310 ISBN 13: 9781698152318
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
£ 42.04
Quantity: Over 20 available
Add to basketPaperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 245.
Seller: preigu, Osnabrück, Germany
Buch. Condition: Neu. Applied Data Science | Lessons Learned for the Data-Driven Business | Martin Braschler (u. a.) | Buch | xiii | Englisch | 2019 | Springer | EAN 9783030118204 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.