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This book focuses on how to use various data mining techniques to develop real-world applications. It offers practical applications with a clear understanding of data mining concepts. The book also has a special chapter on case studies of data mining in practice.
List of contents
Preface. Acknowledgments. Contributors. 1 Introduction to Data Mining. 2 Review of Latent Dirichlet Allocation to Understand Motivations to Share Conspiracy Theory: A Case Study of "Plandemic" during COVID 19. 3 Near Human-Level Style Transfer. 4 Semantics-Based Distributed Document Clustering. 5 Application of Machine Learning in Disease Prediction. 6 Federated Machine Learning-Based Bank Customer Churn Prediction. 7 Challenges and Avenues in the Sophisticated Health-Care System. 8 Unusual Social Media Behavior Detection Using Distributed Data Stream Mining. 9 Market Basket Analysis Using Distributed Algorithm. 10 Identification of Crime Prone-Areas Using Data Mining Techniques. 11 Smart Baby Cradle for Infant Soothing and Monitoring. 12 Word-Level Devanagari Text Recognition. 13 Wall Paint Visualizer Using Panoptic Segmentation. 14 Fashion Intelligence: An Artificial Intelligence-Based Clothing Fashion Stylist. Index.
Summary
This book focuses on how to use various data mining techniques to develop real-world applications. It offers practical applications with a clear understanding of data mining concepts. The book also has a special chapter on case studies of data mining in practice.
