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This book provides a straightforward look at the concepts, algorithms and advantages of Bayesian Deep Learning and Deep Generative Models.
The goal of this book is to examine problems, concerns, and solutions for supporting digital twins with Big Data and Artificial Intelligence (AI). The book also explains how to stream real-time big data on an IoT platform using various ways and strategies.
This book sheds light on the optimisation methods that form the basis of effective communication between... Læs mere
The book collects high-quality original contributions, containing the latest developments or... Læs mere
Industry 4.0 is a revolutionary concept that aims to enhance productivity and profitability in various industries... Læs mere
With detailed case studies and step-by-step implementation guides, this book shows how to build and deploy federated learning systems in real-world scenarios – such as in healthcare, finance, IoT, and edge computing.
Thoroughly revised and updated, this is the first book of the second edition of Introduction to Data Science: Data Wrangling and Visualization with R. It introduces skills that can help you tackle real-world data analysis challenges. No previous knowledge of R is necessary.
Smart cities with various technological innovations have played an important role and influenced society as well. Due... Læs mere
The proposed book is designed as a reference text and provides a comprehensive overview of conceptual and practical knowledge... Læs mere
This book offers practical guidance on how to implement data-driven, accelerated product... Læs mere
Intelligent and sustainable manufacturing employs computer-integrated manufacturing, digital information technology,... Læs mere
Identifying and stopping the dissemination of fabricated news, hate speech, or deceptive information camouflaged as legitimate... Læs mere