Challenges applications data analytics (17 Ergebnisse)

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Taschenbuch. Zustand: Neu. Cloud Computing Applications, Challenges and Data Analytics | Bhasutkar Mahesh | Taschenbuch | 56 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786139957392 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. …

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This timely text/reference reviews the state of the art of big data analytics, with a particular focus on practical applications. An authoritative selection of leading international researchers present detailed analyses of existing trends for storing and analyzing big data, together with valuable insights into the challenges inherent in current approaches and systems. This is further supported by real-world examples drawn from a broad range of application areas, including healthcare, education, and disaster management. The text also covers, typically from an application-oriented perspective, advances in data science in such areas as big data collection, searching, analysis, and knowledge discovery.Topics and features:Discusses a model for data traffic aggregation in 5G cellular networks, and a novel scheme for resource allocation in 5G networks with network slicingExplores methods that use big data in the assessment of flood risks, and apply neural networks techniques to monitor the safety of nuclear power plantsDescribes a system which leverages big data analytics and the Internet of Things in the application of drones to aid victims in disaster scenariosProposes a novel deep learning-based health data analytics application for sleep apnea detection, and a novel pathway for diagnostic models of headache disordersReviews techniques for educational data mining and learning analytics, and introduces a scalable MapReduce graph partitioning approach for high degree verticesPresents a multivariate and dynamic data representation model for the visualization of healthcare data, and big data analytics methods for software reliability assessmentThis practically-focused volume is an invaluable resource for all researchers, academics, data scientists and business professionals involved in the planning, designing, and implementation of big data analytics projects.Dr. Mohammed M. Alaniis an Associate Professor in Computer Engineering and currently is the Provost at Al Khawarizmi International College, Abu Dhabi, UAE.Dr. Hissam Tawfikis a Professor of Computer Science in the School of Computing, Creative Technologies & Engineering at Leeds Beckett University, UK.Dr. Mohammed Saeedis a Professor in Computing and currently is the Vice President for Academic Affairs and Research at the University of Modern Sciences, Dubai, UAE.Dr. Obinna Anyais a Research Staff Member at IBM Research - Almaden, San Jose, CA, USA.…

Taschenbuch. Zustand: Neu. Applications of Big Data Analytics | Trends, Issues, and Challenges | Mohammed M. Alani (u. a.) | Taschenbuch | xii | Englisch | 2019 | Springer | EAN 9783030094973 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

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Hardcover. Zustand: Brand New. 244 pages. 9.21x6.14x0.83 inches. In Stock.

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Zustand: New. Presents the latest advances in Deep Learning for data analytics and biomedical engineering applications. Discusses Deep Learning techniques as they are being applied in the real world of biomedical engineering and data science, including .

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Taschenbuch. Zustand: Neu. Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges | Aboul Ella Hassanien (u. a.) | Taschenbuch | Studies in Big Data | xi | Englisch | 2021 | Springer | EAN 9783030593407 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Buch. Zustand: Neu. Neuware - Earth Observation Data Analytics Using Machine and Deep Learning: Modern tools, applications and challenges covers the basic properties, features and models for Earth observation (EO) recorded by very high-resolution (VHR) multispectral, hyperspectral, synthetic aperture radar (SAR), and multi-temporal observations. Approaches for applying pre-processing methods and deep learning techniques to satellite images for various applications - such as identifying land cover features, object detection, crop classification, target recognition, and the monitoring of earth resources - are described. Cost-efficient resource allocation solutions are provided, which are robust against common uncertainties that occur in annotating and extracting features on satellite images. This book is a valuable resource for engineers and researchers in academia and industry working on AI, machine and deep learning, data science, remote sensing, GIS, SAR, satellite communications, space science, image processing and computer vision. It will also be of interest to staff at research agencies, lecturers and advanced students in related fields. Readers will need a basic understanding of computing, remote sensing, GIS and image interpretation.…

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is intended to present the state of the art in research on machine learning and big data analytics.The accepted chapterscovered many themes including artificial intelligence and data mining applications,machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.…

Taschenbuch. Zustand: Neu. Neuware - Deep learning, a branch of Artificial Intelligence and machine learning, has led to new approaches to solving problems in a variety of domains including data science, data analytics and biomedical engineering. Deep Learning for Data Analytics: Foundations, Biomedical Applications and Challenges provides readers with a focused approach for the design and implementation of deep learning concepts using data analytics techniques in large scale environments. Deep learning algorithms are based on artificial neural network models to cascade multiple layers of nonlinear processing, which aids in feature extraction and learning in supervised and unsupervised ways, including classification and pattern analysis. Deep learning transforms data through a cascade of layers, helping systems analyze and process complex data sets. Deep learning algorithms extract high level complex data and process these complex sets to relatively simpler ideas formulated in the preceding level of the hierarchy. The authors of this book focus on suitable data analytics methods to solve complex real world problems such as medical image recognition, biomedical engineering, and object tracking using deep learning methodologies. The book provides a pragmatic direction for researchers who wish to analyze large volumes of data for business, engineering, and biomedical applications. Deep learning architectures including deep neural networks, recurrent neural networks, and deep belief networks can be used to help resolve problems in applications such as natural language processing, speech recognition, computer vision, bioinoformatics, audio recognition, drug design, and medical image analysis. …

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Hardcover. Zustand: Brand New. 648 pages. 9.50x6.25x1.50 inches. In Stock.