data science big environment (12 Ergebnisse)

viii, 303 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.

Zustand: Sehr gut. Zustand: Sehr gut - Gepflegter, sauberer Zustand. | Seiten: 312 | Sprache: Englisch | Produktart: Bücher.

hardcover. Zustand: Very Good.

Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 400 | Sprache: Englisch | Produktart: Bücher.

Zustand: New. In.

Zustand: New. In English.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This volume teaches readers how to sort through the vast mountain of climate and environmental science data to extract actionable insights. With the advancements in sensing technology, we now observe petabytes of data related to climate and the environment. While the volume of data is impressive, collecting big data for the sake of data alone proves to be of limited utility. Instead, our quest is for actionable data that can drive tangible actions and meaningful impact.Yet, unearthing actionable insights from the accumulated big data and delivering them to global stakeholders remains a burgeoning field. Although traditional data mining struggles to keep pace with data accumulation, scientific evolution has spurred the emergence of new technologies like numeric modeling and machine learning. These cutting-edge tools are now tackling grand challenges in climate and the environment, from forecasting extreme climate events and enhancing environmental productivity to monitoringgreenhouse gas emissions, fostering smart environmental solutions, and understanding aerosols. Additionally, they model environmental-human interactions, inform policy, and steer markets towards a healthier and more environment-friendly direction.While there's no universal solution to address all these formidable tasks, this book takes us on a guided journey through three sections, enriched with chapters from domain scientists. Part I defines actionable science and explores what truly renders data actionable. Part II showcases compelling case studies and practical use scenarios, illustrating these principles in action. Finally, Part III provides an insightful glimpse into the future of actionable science, focusing on the pressing climate and environmental issues we must confront.Embark on this illuminating voyage with us, where big data meets practical research, and discover how our collective efforts move us closer to a sustainable and thriving future. This book is an invitation to unlock the mysteries of our environment, transforming data into decisive action for generations to come.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a comprehensive and up-to-date treatise of a range of methodological and algorithmic issues. It also discusses implementations and case studies, identifies the best design practices, and assesses data analytics business models and practices in industry, health care, administration and business.Data science and big data go hand in hand and constitute a rapidly growing area of research and have attracted the attention of industry and business alike. The area itself has opened up promising new directions of fundamental and applied research and has led to interesting applications, especially those addressing the immediate need to deal with large repositories of data and building tangible, user-centric models of relationships in data. Data is the lifeblood of today's knowledge-driven economy.Numerous data science models are oriented towards end users and along with the regular requirements for accuracy (which are present in any modeling), come the requirements for ability to process huge and varying data sets as well as robustness, interpretability, and simplicity (transparency). Computational intelligence with its underlying methodologies and tools helps address data analytics needs.The book is of interest to those researchers and practitioners involved in data science, Internet engineering, computational intelligence, management, operations research, and knowledge-based systems.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a comprehensive and up-to-date treatise of a range of methodological and algorithmic issues. It also discusses implementations and case studies, identifies the best design practices, and assesses data analytics business models and practices in industry, health care, administration and business.Data science and big data go hand in hand and constitute a rapidly growing area of research and have attracted the attention of industry and business alike. The area itself has opened up promising new directions of fundamental and applied research and has led to interesting applications, especially those addressing the immediate need to deal with large repositories of data and building tangible, user-centric models of relationships in data. Data is the lifeblood of today's knowledge-driven economy.Numerous data science models are oriented towards end users and along with the regular requirements for accuracy (which are present in any modeling), come the requirements for ability to process huge and varying data sets as well as robustness, interpretability, and simplicity (transparency). Computational intelligence with its underlying methodologies and tools helps address data analytics needs.The book is of interest to those researchers and practitioners involved in data science, Internet engineering, computational intelligence, management, operations research, and knowledge-based systems.

Hardcover. Zustand: Brand New. 398 pages. 9.25x6.10x1.02 inches. In Stock.

Hardcover. Zustand: Brand New. 303 pages. 9.25x6.25x1.00 inches. In Stock.