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Soft Computing in Data Science

organized in topical sections on information and customer analytics; visual data science; machine and deep learning; big data analytics;

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Data Science and Visual Computing

Data science addresses the need to extract knowledge and information from data volumes, often from real-time sources in a wide variety;

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Big Data and Visual Analytics

This book provides users with cutting edge methods and technologies in the area of big data and visual analytics, as well as an insight to;

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Smart Data

Smart Data: State-of-the-Art Perspectives in Computing and Applications explores smart data computing techniques to provide intelligent;

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Smart Data

Smart Data: State-of-the-Art Perspectives in Computing and Applications explores smart data computing techniques to provide intelligent;

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EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing

computing and its self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mirror the way the human;

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2nd EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing

computing and its self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mirror the way the human;

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Scientific Computing

Computational Science and Applications Scientific Computing + Data Management + Cryptography Novel Scientific And Engineering Algorithms and;

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Low Rank and Sparse Modeling for Visual Analysis

and learning among unconstrained visual data. The book includes chapters covering multiple emerging topics in this new field. It links;

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Data Science and Security

learning, computer vision, algorithms design, computer networking, data mining, big data, text mining, knowledge representation, soft computing and;

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Application of Visual Data in K-16 Science Classrooms

includes discussion about the current state of the art with respect to science classroom application and utilization of the particular visual data;

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Application of Visual Data in K-16 Science Classrooms

includes discussion about the current state of the art with respect to science classroom application and utilization of the particular visual data;

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Computational Social Science

technology, especially sweeping progress in the Internet of things, cloud computing, social networks, social media and big data, social computing, as;

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Intelligent Computing Theories and Technology

in topical sections on systems biology and computational biology; cognitive science and computational neuroscience; knowledge discovery and data;

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Visual Data in Science Education

relates to education, and highlighted the breadth of types and uses of visual data across the major academic disciplines. In this book, the;

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Visual Data in Science Education

relates to education, and highlighted the breadth of types and uses of visual data across the major academic disciplines. In this book, the;

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Cloud Computing with e-Science Applications

substantial amounts of data must be captured, communicated, aggregated, stored, and analyzed. Cloud Computing with e-Science Applications explains how;

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Cloud Computing with E-Science Applications

substantial amounts of data must be captured, communicated, aggregated, stored, and analyzed. Cloud Computing with e-Science Applications explains how;

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Urban Computing

congestion. Using today's large-scale computing infrastructure and data gathered from sensing technologies, urban computing combines computer science;

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Computer Science and its Applications

applications, including ubiquitous computing, U-Health care system, Big Data, UI/UX for human-centric computing, Computing Service, Bioinformatics and;

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Data Science

This book contains 16 chapters by researchers working in various fields of data science. They focus on theory and applications in language;

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Concise Guide to Computing Foundations

mechanics of materials, geographic information systems, flow analysis, the solving of equations, curve fitting, optimization, and scientific data;

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Concise Guide to Computing Foundations

mechanics of materials, geographic information systems, flow analysis, the solving of equations, curve fitting, optimization, and scientific data;

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Soft Computing for Knowledge Discovery and Data Mining

Data Mining is the science and technology of exploring large and complex bodies of data in order to discover useful patterns. It;

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Big Data Analytics for Sustainable Computing

Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore;

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Cognitive Computing Using Green Technologies

in Robotics, Computer Science, Wireless Networks, and Deep Learning. It goes on to present empirical data and research techniques, modelling;

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Metasynthetic Computing and Engineering of Complex Systems

, complex behavioural and social problems, and actionable knowledge discovery and delivery in the big data era. * Discusses ubiquitous intelligence;

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