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Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization;
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in health sciences and biomedical data. The book is useful for those working with big data analytics in biomedical research, medical industries, and;
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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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the vast quantities of data. In Cloud and Big Data Analytics, the two areas of Swarm Intelligence and Deep Learning are a developing type;
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Big Data Analytics for Intelligent Healthcare Management covers both the theory and application of hardware platforms and architectures;
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value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this;
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value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this;
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, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding;
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This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2021) is intended to be used as a reference book for;
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analytics and Hadoop and Spark programming. Part 1 focuses on data science, the roles of clouds and IoT devices and frameworks for big-data;
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Artificial Intelligence and Big Data Analytics for Smart Healthcare serves as a key reference for practitioners and experts involved;
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This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications;
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machine learning models. Updated case studies from global healthcare providers showcase the use of big data and AI in the fight against chronic;
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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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a variety of structured, unstructured, and semi-structured data. Machine Learning for Healthcare Analytics Projects is packed with new;
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sections named: big data analytics: vision and perspectives; financial data analytics and data streams; web and social media data; big data systems;
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them to gain better insight from this data in order to improve healthcare outcomes. This book is a complete overview of machine learning for;
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Machine Learning for Subsurface Characterization develops and applies neural networks, random forests, deep learning, unsupervised learning;
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analytics, disease network analysis, and techniques for big data Analytics and health information technology.;
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This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and;
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This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and;
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This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and;
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: Visually Impaired Disease Diagnosis and Treatment options Applications of Big Data and Deep Learning in Healthcare Drug;
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of this book is to provide awareness of algorithms used for machine learning and big data in the academic and professional community. The 17;
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and use-cases of Apache Spark 2.x, this Learning Path is ideal for you. Big data professionals who want to learn how to integrate and use the;
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Machine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data;
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learning, and fuzzy logic, this book is ideally designed for students, government officials, data scientists, managers, consultants, analysts, IT;
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