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Clustering Methods for Big Data Analytics - Techniques, Toolboxes and Applications (Hardcover, 1st ed. 2019): Olfa Nasraoui,... Clustering Methods for Big Data Analytics - Techniques, Toolboxes and Applications (Hardcover, 1st ed. 2019)
Olfa Nasraoui, Chiheb-Eddine Ben N'Cir
R4,234 Discovery Miles 42 340 Ships in 12 - 19 working days

This book highlights the state of the art and recent advances in Big Data clustering methods and their innovative applications in contemporary AI-driven systems. The book chapters discuss Deep Learning for Clustering, Blockchain data clustering, Cybersecurity applications such as insider threat detection, scalable distributed clustering methods for massive volumes of data; clustering Big Data Streams such as streams generated by the confluence of Internet of Things, digital and mobile health, human-robot interaction, and social networks; Spark-based Big Data clustering using Particle Swarm Optimization; and Tensor-based clustering for Web graphs, sensor streams, and social networks. The chapters in the book include a balanced coverage of big data clustering theory, methods, tools, frameworks, applications, representation, visualization, and clustering validation.

Clustering Methods for Big Data Analytics - Techniques, Toolboxes and Applications (Paperback, Softcover reprint of the... Clustering Methods for Big Data Analytics - Techniques, Toolboxes and Applications (Paperback, Softcover reprint of the original 1st ed. 2019)
Olfa Nasraoui, Chiheb-Eddine Ben N'Cir
R4,348 Discovery Miles 43 480 Ships in 10 - 15 working days

This book highlights the state of the art and recent advances in Big Data clustering methods and their innovative applications in contemporary AI-driven systems. The book chapters discuss Deep Learning for Clustering, Blockchain data clustering, Cybersecurity applications such as insider threat detection, scalable distributed clustering methods for massive volumes of data; clustering Big Data Streams such as streams generated by the confluence of Internet of Things, digital and mobile health, human-robot interaction, and social networks; Spark-based Big Data clustering using Particle Swarm Optimization; and Tensor-based clustering for Web graphs, sensor streams, and social networks. The chapters in the book include a balanced coverage of big data clustering theory, methods, tools, frameworks, applications, representation, visualization, and clustering validation.

Machine Learning and Data Analytics for Solving Business Problems - Methods, Applications, and Case Studies (Hardcover, 1st ed.... Machine Learning and Data Analytics for Solving Business Problems - Methods, Applications, and Case Studies (Hardcover, 1st ed. 2022)
Bader Alyoubi, Chiheb-Eddine Ben N'Cir, Ibraheem Alharbi, Anis Jarboui
R4,022 Discovery Miles 40 220 Ships in 12 - 19 working days

This book presents advances in business computing and data analytics by discussing recent and innovative machine learning methods that have been designed to support decision-making processes. These methods form the theoretical foundations of intelligent management systems, which allows for companies to understand the market environment, to improve the analysis of customer needs, to propose creative personalization of contents, and to design more effective business strategies, products, and services. This book gives an overview of recent methods - such as blockchain, big data, artificial intelligence, and cloud computing - so readers can rapidly explore them and their applications to solve common business challenges. The book aims to empower readers to leverage and develop creative supervised and unsupervised methods to solve business decision-making problems.

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