Graph Neural Networks by Pethuru Raj Chelliah (.ePUB)+

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File Size: 39.8 MB

Graph Neural Networks: Essentials and Use Cases by Pethuru Raj Chelliah, Pawan Whig, Susila Nagarajan, Usha Sakthivel, Nikhitha Yathiraju
Requirements: .ePUB, .PDF reader, 39.8 MB
Overview: This book explains the technologies and tools that underpin GNNs, offering a clear and practical guide to their industrial applications and use cases. AI engineers, data scientists, and researchers in AI and graph theory will find detailed insights into the latest trends and innovations driving this dynamic field. With practical chapters demonstrating how GNNs are reshaping various industry verticals—and how they complement advances in generative, agentic, and physical AI—this book is an essential resource for understanding and leveraging their potential. The neural network paradigm has surged in popularity for its ability to uncover hidden patterns within vast datasets. This transformative technology has spurred global innovations, particularly through the evolution of deep neural networks (DNNs). Convolutional neural networks (CNNs) have revolutionized computer vision, while recurrent neural networks (RNNs) and their advanced variants have automated natural language processing tasks such as speech recognition, translation, and content generation.
Genre: Non-Fiction > Tech & Devices

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