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Multimodal Analytics for Next-Generation Big Data Technologies and Applications

This edited book will serve as a source of reference for technologies and applications for multimodality data analytics in big data;

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Next Generation Big Data

enterprise big data. The book covers not only the main technology stack but also the next-generation tools and applications used for big data;

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Big Data

methods for scientific and social discovery. It covers fundamental issues about Big Data, including efficient algorithmic methods to process data;

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Big Data

methods for scientific and social discovery. It covers fundamental issues about Big Data, including efficient algorithmic methods to process data;

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Big Data Technologies and Applications

Technologies, includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second;

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Distributed Computing in Big Data Analytics

Big data technologies are used to achieve any type of analytics in a fast and predictable way, thus enabling better human and machine level;

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Big Data Analytics for Internet of Things

BIG DATA ANALYTICS FOR INTERNET OF THINGS Discover the latest developments in IoT Big Data with a new resource from established and;

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Big-Data Analytics for Cloud, IoT and Cognitive Computing

The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main;

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Internet of Things and Big Data Analytics for Smart Generation

This book discusses emerging technologies in the field of the Internet of Things and big data, an area that will be scaled in next two;

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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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Analytics and Data Science

technologies in various domains are still evolving. For instance, the explosive growth in big data and social media analytics requires examination;

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Fog Data Analytics for IoT Applications

) has generated significant amount of heterogeneous and multimodal data, known as big data. To deal with this big data, we require efficient and;

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Machine Learning and Big Data Analytics Paradigms

big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data;

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Feature Engineering for Machine Learning and Data Analytics

media data. It also contains generic feature generation approaches, as well as methods for generating tried-and-tested, hand-crafted, domain;

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Feature Engineering for Machine Learning and Data Analytics

data. It also contains generic feature generation approaches, as well as methods for generating tried-and-tested, hand-crafted, domain-specific;

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Next Generation Sequencing and Data Analysis

applications. The reader learns how to perform Next Generation Sequencing data analysis, how to interpret and visualize the data, and acquires;

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Artificial Intelligence and Big Data Analytics for Smart Healthcare

Artificial Intelligence and Big Data Analytics for Smart Healthcare serves as a key reference for practitioners and experts involved;

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Deep Learning and Edge Computing Solutions for High Performance Computing

identification, object tracking, human action recognition, and cross-modal and multimodal data analysis. High performance computing systems for;

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Big Data Analytics for Large-Scale Multimedia Search

, interactive interfaces for big multimedia and medical decision support applications using large multimodal data. Addresses the area;

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Internet of Things and Big Data Technologies for Next Generation Healthcare

strategies for IoT and big data.;

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Handbook of Big Data Analytics: Applications in ICT, security and business analytics

work is aimed at providing a unique platform for researchers, engineers, developers, educators and advanced students in the field of Big Data;

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Big Data Analytics

. The fourth part of the book examines analytics for marketing decision-making and the roles of big data analytics for market intelligence and;

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Big Data Analytics

. The fourth part of the book examines analytics for marketing decision-making and the roles of big data analytics for market intelligence and;

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Data Science and Analytics

submissions. The papers are organized in topical sections on big data analysis, data centric programming, next generation computing, social and web;

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Data Science and Analytics

generation computing; social and web analytics; security in data science analytics; big data analytics.;

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Data Science and Analytics

generation computing; social and web analytics; security in data science analytics; big data analytics.;

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Advances in Big Data

, depicts an interesting collaborative adventure of neural networks with big data and other learning technologies.;

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