big data analytics digital (30 Ergebnisse)

Paperback. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

paperback. Zustand: Good.

paperback. Zustand: Very Good.

Paperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Zustand: Like New. Most items will be dispatched the same or the next working day. An apparently unread copy in perfect condition. Dust cover is intact with no nicks or tears. Spine has no signs of creasing. Pages are clean and not marred by notes or folds of any kind.

Zustand: New. pp. 150.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.

Taschenbuch. Zustand: Neu. Neuware - The book is about use of AI in Big Data Analytics and has the potential for positive impact and global implications in healthcare. Future details on the use of Big Data in medical facilities, the definition of strategies adopted by medical facilities to promote and implement such solutions, as well as the benefits they gain from the use of Big Data analysis and how the perspectives in this area are seen. The interesting part in the book is How AI-powered facial emotion recognition device redefines patient care which is a device that is developed by the author which is going to be ground breaking in terms of technology.

Paperback. Zustand: Brand New. 262 pages. 9.18x6.12x9.21 inches. In Stock.

Zustand: New.

Zustand: New. This in-depth guide provides managers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, and the dangers of these technologies. Written in an accessible style, Steven Finlay provides a contextual roadmap for developing solutions that deliver benefits to organizations. Series: Business in the Digital Economy. Num Pages: 272 pages, biography. BIC Classification: KCM; KJC; KJMV3; KJQ; KJS; KJSM. Category: (G) General (US: Trade). Dimension: 161 x 239 x 17. Weight in Grams: 412. . 2014. 1st ed. 2014. paperback. . . . . Books ship from the US and Ireland.

Zustand: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.

Zustand: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

Hardcover. Zustand: Brand New. 246 pages. 9.75x6.50x0.75 inches. In Stock.

Zustand: New. 2025. hardcover. . . . . . Books ship from the US and Ireland.

Hardcover. Zustand: Brand New. 213 pages. 9.25x6.00x0.75 inches. In Stock.

Zustand: New.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In the dynamic realm of digital agriculture, the integration of big data acquisition platforms has sparked both curiosity and enthusiasm among researchers and agricultural practitioners. This book embarks on a journey to explore the intersection of artificial intelligence and agriculture, focusing on small-unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), edge-AI sensors and the profound impact they have on digital agriculture, particularly in the context of heterogeneous crops, such as walnuts, pomegranates, cotton, etc. For example, lightweight sensors mounted on UAVs, including multispectral and thermal infrared cameras, serve as invaluable tools for capturing high-resolution images. Their enhanced temporal and spatial resolutions, coupled with cost effectiveness and near-real-time data acquisition, position UAVs as an optimal platform for mapping and monitoring crop variability in vast expanses. This combination of data acquisition platforms and advanced analytics generates substantial datasets, necessitating a deep understanding of fractional-order thinking, which is imperative due to the inherent 'complexity' and consequent variability within the agricultural process. Much optimism is vested in the field of artificial intelligence, such as machine learning (ML) and computer vision (CV), where the efficient utilization of big data to make it 'smart' is of paramount importance in agricultural research. Central to this learning process lies the intricate relationship between plant physiology and optimization methods. The key to the learning process is the plant physiology and optimization method. Crafting an efficient optimization method raises three pivotal questions: 1.) What represents the best approach to optimization 2.) How can we achieve a more optimal optimization 3.) Is it possible to demand 'more optimal machine learning,' exemplified by deep learning, while minimizing the need for extensive labeled data for digital agriculture This book details the foundations of the plant physiology-informed machine learning (PPIML) and the principle of tail matching (POTM) framework. It is the 9th title of the 'Agriculture Automation and Control' book series published by Springer.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In the dynamic realm of digital agriculture, the integration of big data acquisition platforms has sparked both curiosity and enthusiasm among researchers and agricultural practitioners. This book embarks on a journey to explore the intersection of artificial intelligence and agriculture, focusing on small-unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), edge-AI sensors and the profound impact they have on digital agriculture, particularly in the context of heterogeneous crops, such as walnuts, pomegranates, cotton, etc. For example, lightweight sensors mounted on UAVs, including multispectral and thermal infrared cameras, serve as invaluable tools for capturing high-resolution images. Their enhanced temporal and spatial resolutions, coupled with cost effectiveness and near-real-time data acquisition, position UAVs as an optimal platform for mapping and monitoring crop variability in vast expanses. This combination of data acquisition platforms and advanced analytics generates substantial datasets, necessitating a deep understanding of fractional-order thinking, which is imperative due to the inherent 'complexity' and consequent variability within the agricultural process. Much optimism is vested in the field of artificial intelligence, such as machine learning (ML) and computer vision (CV), where the efficient utilization of big data to make it 'smart' is of paramount importance in agricultural research. Central to this learning process lies the intricate relationship between plant physiology and optimization methods. The key to the learning process is the plant physiology and optimization method. Crafting an efficient optimization method raises three pivotal questions: 1.) What represents the best approach to optimization 2.) How can we achieve a more optimal optimization 3.) Is it possible to demand 'more optimal machine learning,' exemplified by deep learning, while minimizing the need for extensive labeled data for digital agriculture This book details the foundations of the plant physiology-informed machine learning (PPIML) and the principle of tail matching (POTM) framework. It is the 9th title of the 'Agriculture Automation and Control' book series published by Springer.

Hardcover. Zustand: Brand New. 257 pages. 9.25x6.10x0.63 inches. In Stock.

Taschenbuch. Zustand: Neu. Neuware -This book is about turning data into smart decisions, knowledge into wisdom and business into business intelligence and insight. It explores diverse paradigms, methodologies, models, tools and techniques of the emerging knowledge domain of digitalized business analytics applications.The book covers almost every crucial aspect of applied artificial intelligence in business, smart mobile and digital services in business administration, marketing, accounting, logistics, finance and IT management.This book aids researchers, practitioners and decisions makers to gain enough knowledge and insight on how to effectively leverage data into competitive intelligence.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 752 pp. Englisch.

Buch. Zustand: Neu. Neuware -This book is about turning data into smart decisions, knowledge into wisdom and business into business intelligence and insight. It explores diverse paradigms, methodologies, models, tools and techniques of the emerging knowledge domain of digitalized business analytics applications.The book covers almost every crucial aspect of applied artificial intelligence in business, smart mobile and digital services in business administration, marketing, accounting, logistics, finance and IT management.This book aids researchers, practitioners and decisions makers to gain enough knowledge and insight on how to effectively leverage data into competitive intelligence.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 752 pp. Englisch.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is about turning data into smart decisions, knowledge into wisdom and business into business intelligence and insight. It explores diverse paradigms, methodologies, models, tools and techniques of the emerging knowledge domain of digitalized business analytics applications.The book covers almost every crucial aspect of applied artificial intelligence in business, smart mobile and digital services in business administration, marketing, accounting, logistics, finance and IT management.This book aids researchers, practitioners and decisions makers to gain enough knowledge and insight on how to effectively leverage data into competitive intelligence.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is about turning data into smart decisions, knowledge into wisdom and business into business intelligence and insight. It explores diverse paradigms, methodologies, models, tools and techniques of the emerging knowledge domain of digitalized business analytics applications.The book covers almost every crucial aspect of applied artificial intelligence in business, smart mobile and digital services in business administration, marketing, accounting, logistics, finance and IT management.This book aids researchers, practitioners and decisions makers to gain enough knowledge and insight on how to effectively leverage data into competitive intelligence.

Paperback. Zustand: Brand New. 751 pages. 9.26x6.10x1.50 inches. In Stock.

Hardcover. Zustand: Brand New. 739 pages. 9.75x6.50x1.75 inches. In Stock.

Hardcover. Zustand: Brand New. 306 pages. German language. 9.25x6.10x0.91 inches. In Stock.

Taschenbuch. Zustand: Neu. Neuware -Masterarbeit aus dem Jahr 2022 im Fachbereich Informatik - Wirtschaftsinformatik, Note: 1,0, Ferdinand Porsche FernFH, Sprache: Deutsch, Abstract: Das Ziel dieser Arbeit ist es, ein potentielle Verbesserung im Bereich Lean Management, genauer Shopfloor Management, zu entwickeln. Die Forschungsfrage der Masterthesis lautet: Wie können produzierende Unternehmen durch Big Data Analytics im Bereich des Shopfloor Managements Verbesserungspotentiale erzielen Im Genaueren wird in dieser Arbeit ein praxisbezogenes Verbesserungspotential erarbeitet, mit welchem Unternehmen und Organisationen die Lücke zwischen analogem und digitalem Shopfloor Management schließen können. Es wird dargestellt, wie wichtig definierte Kennzahlen für eine konsistente Entscheidungsfindung sind. Zusätzlich wird aufgezeigt, wie Beschäftigte im Spannungsfeld von Digitalisierung und Industrie 4.0 mithilfe eines visuellen Informationssystems in digitale Prozesslandschaften eingebunden werden können. Diese Masterthesis wurde bei einem deutschen Luftfahrtlogistikunternehmen durchgeführt, welches ein breites Spektrum an Logistikkomplettlösungen anbietet. Das Prinzip des (analogen) Shopfloor Managements wird hier konsequent angewendet, um im Spannungsfeld von stringenten Luftfahrtregularien und hohem Wettbewerbsdruck zu bestehen. Dabei fällt auf, dass die Erstellung der KPIs meist weder automatisiert noch standardisiert, sondern analog abläuft. Das Ergebnis ist ein hoher manueller Aufwand, hohes Fehlerpotential und ein geringer Grad an Transparenz für Beschäftigte und Führungskräfte. Aus diesem Grund lag es nahe, ein Projekt mit dem Ziel, Verbesserungspotentiale herauszustellen, zu initiieren.Books on Demand GmbH, Überseering 33, 22297 Hamburg 124 pp. Deutsch.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Masterarbeit aus dem Jahr 2022 im Fachbereich Informatik - Wirtschaftsinformatik, Note: 1,0, Ferdinand Porsche FernFH, Sprache: Deutsch, Abstract: Das Ziel dieser Arbeit ist es, ein potentielle Verbesserung im Bereich Lean Management, genauer Shopfloor Management, zu entwickeln. Die Forschungsfrage der Masterthesis lautet: Wie können produzierende Unternehmen durch Big Data Analytics im Bereich des Shopfloor Managements Verbesserungspotentiale erzielen Im Genaueren wird in dieser Arbeit ein praxisbezogenes Verbesserungspotential erarbeitet, mit welchem Unternehmen und Organisationen die Lücke zwischen analogem und digitalem Shopfloor Management schließen können. Es wird dargestellt, wie wichtig definierte Kennzahlen für eine konsistente Entscheidungsfindung sind. Zusätzlich wird aufgezeigt, wie Beschäftigte im Spannungsfeld von Digitalisierung und Industrie 4.0 mithilfe eines visuellen Informationssystems in digitale Prozesslandschaften eingebunden werden können. Diese Masterthesis wurde bei einem deutschen Luftfahrtlogistikunternehmen durchgeführt, welches ein breites Spektrum an Logistikkomplettlösungen anbietet. Das Prinzip des (analogen) Shopfloor Managements wird hier konsequent angewendet, um im Spannungsfeld von stringenten Luftfahrtregularien und hohem Wettbewerbsdruck zu bestehen. Dabei fällt auf, dass die Erstellung der KPIs meist weder automatisiert noch standardisiert, sondern analog abläuft. Das Ergebnis ist ein hoher manueller Aufwand, hohes Fehlerpotential und ein geringer Grad an Transparenz für Beschäftigte und Führungskräfte. Aus diesem Grund lag es nahe, ein Projekt mit dem Ziel, Verbesserungspotentiale herauszustellen, zu initiieren.