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Condizione: Gebraucht - Wie neu. Neu und Originalverpackt - vdf Verlag - h4.

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New. In English.

Condizione: 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.…

Condizione: New.

Hardback. Condizione: New. 2019 ed. 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.…

Buch. Condizione: 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.…

Condizione: New.

Hardcover. Condizione: Brand New. 465 pages. 9.25x6.25x1.25 inches. In Stock.

Condizione: New.

Hardback. Condizione: New. 2019 ed. 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.…

Hardcover. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condizione: Gut. 148 S. ; 25 cm Aus der Bibliothek von Prof. Wolfgang Haase, langjährigem Herausgeber der ANRW und des International Journal of the Classical Tradition (IJCT) / From the library of Prof. Wolfgang Haase, long-time editor of ANRW and the International Journal of the Classical Tradition (IJCT). - sehr guter Zustand - Inhalt -- Vorwort -- Ulrich Siegele -- Absolutismus und Aufklärung in Kursachsen. Johann Christoph Gottsched und der Leipziger Bürgermeister Gottfried Lange (1672-1748) -- Ludwig Stockinger -- Gottscheds Stellung in der deutschen Literaturgeschichte -- Hans Poser -- Gottsched und die Philosophie der deutschen Aufklärung -- Adolf Dresen -- Hanswursts Immerwiederkehr. Die Leipziger Liaison von Literatur und Theater -- Kurt Sier -- Gottsched und die Antike -- Detlef Döring -- Johann Christoph Gottsched und die Deutsche Gesellschaft zu Leipzig -- Gotthard Lerchner -- Gottscheds sprachgeschichtliche Bedeutung. ISBN 9783777612140 Sprache: Deutsch Gewicht in Gramm: 452 Originalhardcover mit Schutzumschlag.…

Kartoniert / Broschiert. Condizione: New. Preiswerte kleine Sensoren in Tracking-Geraeten und Smartphones machen es moeglich: die staendige Ueberwachung der Fitness, Wellness oder Gesundheit. Quantified Self , das Messen der eigenen Koerper- und Verhaltensaktivitaeten, findet immer mehr Verbreitung. Anw. …

Condizione: new. Questo è un articolo print on demand.

Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 480 pp. Englisch.…

Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Systematically highlights the connection between theory, on the one end, and its application in specific use cases, on the otherEach chapter describes a fundamental principle, method or tool in data science by analyzing specif. …

Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 480 pp. Englisch.…

Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND.