Applied Deep Learning on Graphs: Leveraging Graph Data to Generate Impact Using Specialized Deep Learning Architectures

Lakshya Khandelwal

Subhajoy Das

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eBook Dec 2024 1st Edition

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Key benefits

Explore Graph Data in real-world systems and leverage Graph Learning for impactful business results

Dive deep into popular and specialized graph Deep neural architectures

Learn to build scalable and Productionizable Graph Learning solutions

Description

This book provides a comprehensive journey into graph neural networks, guiding readers from foundational concepts all the way to advanced techniques and cutting-edge applications. We begin by motivating why graph data structures are ubiquitous in the era of interconnected information, and why we require specialized deep learning approaches, explaining challenges and with existing methods. Next, readers learn about early graph representation techniques like DeepWalk and node2vec which paved the way for modern advances. The core of the book dives deep into popular graph neural architectures – from essential concepts in graph convolutional and attentional networks to sophisticated autoencoder models to leveraging LLMs and technologies like Retrieval augmented generation on Graph data. With strong theoretical grounding established, we then transition to practical implementations, covering critical topics of scalability, interpretability and key application domains like NLP, recommendations, computer vision and more. By the end of this book, readers master both underlying ideas and hands-on coding skills on real-world use cases and examples along the way. Readers grasp not just how to effectively leverage graph neural networks today but also the promising frontiers to influence where the field may evolve next.

What you will learn

Discover extracting business value through a graph-centric approach

Develop a basic intuition of learning graph attributes using Machine Learning

Explore limitations of traditional Deep Learning with graph data and delve into specialized graph-based architectures

Learn how Graph Deep Learning finds applications in industry, including Recommender Systems, NLP, etc

Grasp challenges in production such as scalability and interpretability

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Free for first 7 days. $19.99 p/m after that. Cancel any time!

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50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.

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Applied Deep Learning on Graphs: Leveraging Graph Data to Generate Impact Using Specialized Deep Learning Architectures

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