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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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Advances on Smart and Soft Computing

, big data analytics, smart computing, smart cities, Internet of things (IoT), data communication, cloud computing, machine learning algorithms;

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

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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Intelligent Systems

computing, IoT and applications in smart environments, smart health, smart city, wireless networks, big data, cloud computing, business intelligence;

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Innovative Data Communication Technologies and Application

, communication security, machine learning, informatics, mobile computing, cloud computing and big data analytics. The best selected papers, presented at;

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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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Intelligent and Cloud Computing

and monitoring for cloud management, machine learning, data mining for cloud computing, data-driven methodology and architecture, and;

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Intelligent and Cloud Computing

and monitoring for cloud management, machine learning, data mining for cloud computing, data-driven methodology and architecture, and;

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Security and Privacy for Big Data, Cloud Computing and Applications

As big data becomes increasingly pervasive and cloud computing utilization becomes the norm, the security and privacy of our systems and;

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Machine Learning Technologies and Applications

intelligence, machine learning, data mining and big data computing, cloud computing, Internet of things, distributed computing and smart systems.;

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Smart Data

contributions from leading experts and covers cutting-edge topics such as smart data and cloud computing, AI for networking, smart data deep learning;

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Smart Data

contributions from leading experts and covers cutting-edge topics such as smart data and cloud computing, AI for networking, smart data deep learning;

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Official Google Cloud Certified Professional Data Engineer Study Guide

Dan Sullivan, a popular and experienced online course author for machine learning, big data, and Cloud topics, Google Cloud Certified Professional Data;

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Innovations in Computer Science and Engineering

research in data science and analytics, cloud computing, machine learning, data mining, big data and analytics, information security and privacy;

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Big Data Analytics for Sustainable Computing

learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational;

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Pervasive Systems, Algorithms and Networks

submissions. The papers focus on all aspects of: big data analytics & machine learning; cyber security; cloud fog & edge computing; communication;

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Soft Computing Systems

organized in topical sections on soft computing, evolutionary algorithms, image processing, deep learning, artificial intelligence, big data;

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Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021)

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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Cloud Analytics with Microsoft Azure

data. As you advance, you'll learn to build an end-to-end analytics pipeline on the cloud with machine learning and deep learning concepts. By;

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Proceedings of International Joint Conference on Computational Intelligence

, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and;

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Managing Distributed Cloud Applications and Infrastructure

clouds and discusses how data analytics and machine learning, application and infrastructure optimization, and simulation can deliver quality;

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Artificial Intelligence Algorithms and Applications

control, big data and cloud computing, deep learning, and hybrid machine learning systems.The papers are organized according to the following;

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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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Artificial Intelligence and Machine Learning for EDGE Computing

Data, Artificial Intelligence, Machine Learning and distributed computing, may it be Cloud Computing or the evolving Fog and Edge Computing;

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Applications of Big Data in Large- and Small-Scale Systems

this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large;

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Applications of Big Data in Large- and Small-Scale Systems

this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large;

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Big Data, IoT, and Machine Learning

of Machine Learning, and Section II addresses issues about Big Data, the Cloud and the Internet of Things. This brings all the related technologies;

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