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Deep Learning Techniques and Optimization Strategies in Big Data Analytics

Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning;

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Deep Learning for Data Analytics

Learning for data analytics and biomedical engineering applications.Discusses Deep Learning techniques as they are being applied in the;

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Big Data Analytics for Intelligent Healthcare Management

, the development of software methods, techniques and tools, applications and governance, and adoption strategies for the use of big data;

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Machine Learning and Big Data Analytics Paradigms

This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered;

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Big Data Analytics Methods

Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers;

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Data Science Solutions with Python

Apply supervised and unsupervised learning to solve practical and real-world big data problems. This book teaches you how to engineer;

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Signal Processing and Networking for Big Data Applications

This unique text helps make sense of big data in engineering applications using tools and techniques from signal processing. It presents;

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Applications of Machine Learning in Big-Data Analytics and Cloud Computing

. New Cloud Computing and Big Data tools endow researchers and analysts with novel techniques and opportunities to collect, manage and analyze;

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Big Data Analytics for Internet of Things

techniques to unearth valuable insights from IoT data and offers novel designs for IoT systems. With an abiding focus on practical strategies with;

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Advanced Data Analytics for Power Systems

learning, big data analytics, graph theory, and game theory, this is an essential resource for graduate students and researchers in academia and;

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Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization;

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Healthcare Data Analytics and Management

, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding;

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Proceedings of International Conference on Data Science and Applications

, bioinformatics and systems, artificial neural networks, deep learning, genetic algorithms, data mining, fuzzy logic, optimization algorithms, image;

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Advances in Big Data Analytics

of big data analytics and/or data science, multi-criteria optimization for learning, expert and rule-based data analysis, support vector machines;

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Multimodal Analytics for Next-Generation Big Data Technologies and Applications

data; unsupervised learning strategies for big multimodal data; supervised learning strategies for big multimodal data; and multimodal big data;

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Advanced Deep Learning Applications in Big Data Analytics

develop new architecture and applications of deep learning algorithms in big data and the IoT. Highlighting a wide range of topics such as;

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Advanced Data Analytics Using Python

using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural;

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Advanced Data Analytics Using Python

using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural;

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Deep Learning and Edge Computing Solutions for High Performance Computing

analytics, disease network analysis, and techniques for big data Analytics and health information technology.;

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IoT-Based Data Analytics for the Healthcare Industry

IoT Based Data Analytics for the Healthcare Industry: Techniques and Applications explores recent advances in the analysis of healthcare;

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Data Analytics in Biomedical Engineering and Healthcare

Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analytics, machine learning, and deep learning;

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Data Science and Predictive Analytics

, contemporary learning-based data science techniques, computational algorithm development, optimization theory, statistical computing, and biomedical;

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Engineering Analytics

used to improve performance tracking, customer segmentation for resource optimization, patterns and classification strategies, and logistics;

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Big-Data Analytics for Cloud, IoT and Cognitive Computing

computing. Big data analytics and cognitive machine learning, as well as cloud architecture, IoT and cognitive systems are explored, and mobile;

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Harness Big Data With Analytics

complete view of big data and analytics techniques as they are applied to the oil and gas industry. Including a compendium of specific case studies;

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Optimizing Big Data Management and Industrial Systems With Intelligent Techniques

In order to survive an increasingly competitive market, corporations must adopt and employ optimization techniques and big data analytics;

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Applied Data Analytics

- Principles and Applications seeks to bridge this missing gap by providing some of the most sought after techniques in big data analytics;

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