Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Applied Deep Learning on Graphs

You're reading from Applied Deep Learning on Graphs Leveraging Graph Data to Generate Impact Using Specialized Deep Learning Architectures

Product type Paperback

Published in Dec 2024

Publisher Packt

ISBN-13 9781835885963

Length

Edition 1st Edition

Concepts

Data Governance

Authors (2):

Lakshya Khandelwal

Subhajoy Das

View More author details

Table of Contents (19) Chapters

Preface

1. Part 1: Foundations of Graph Learning FREE CHAPTER

2. Chapter 1: Introduction to Graph Learning

3. Chapter 2: Graph Learning in the Real World

4. Chapter 3: Graph Representation Learning

5. Part 2: Advanced Graph Learning Techniques

6. Chapter 4: Deep Learning Models for Graphs

7. Chapter 5: Graph Deep Learning Challenges

8. Chapter 6: Harnessing Large Language Models for Graph Learning

9. Part 3: Practical Applications and Implementation

10. Chapter 7: Graph Deep Learning in Practice

11. Chapter 8: Graph Deep Learning for Natural Language Processing

12. Chapter 9: Building Recommendation Systems Using Graph Deep Learning

13. Chapter 10: Graph Deep Learning for Computer Vision

14. Part 4: Future Directions

15. Chapter 11: Emerging Applications

16. Chapter 12: The Future of Graph Learning

17. Index

Why subscribe?

18. Other Books You May Enjoy

Potential breakthroughs and long-term vision

As we explore the frontier of artificial intelligence, it’s crucial to consider the potential breakthroughs and long-term vision that could shape the future of this field.

Artificial general intelligence and graphs

Graph representations could play a crucial role in the development of artificial general intelligence (AGI).

The role of graph representations in AGI

Researchers are exploring how graph-structured knowledge and reasoning could contribute to more general and flexible AI systems. Graph representations offer a natural way to model complex relationships and hierarchies, which is essential for human-like reasoning. For example, the Neuro-Symbolic Concept Learner combines GNNs with symbolic reasoning to learn concepts and relationships from visual scenes, demonstrating a potential path toward more general AI systems.

Graph-based world models are being developed to enable AI systems to build and maintain internal...

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at $19.99/month. Cancel anytime

Authors (2)

Lakshya Khandelwal

Lakshya Khandelwal

Lakshya is currently leading several Natural Language, forecasting and recommendation system initiatives in Walmart, building next generation AI products for Millions of customers. Lakshya holds a Bachelors and Masters degree from IIT Kanpur in Mathematics and Computer Science and has 8+ years of experience in building Scalable Machine Learning Products for multiple Tech Giants. Before joining Walmart, Lakshya worked as a Data Scientist with Adobe, building Search Bid optimization solutions as part of the advertising cloud suite with major enterprises across the globe as customers. Prior to Adobe, he worked as a Lead ML Engineer with Samsung building Natural Language intelligence for the very first version of Bixby used by millions of users daily.

See other products by Lakshya Khandelwal

Subhajoy Das

Subhajoy Das

Subhajoy is a Staff Data Scientist with seven years of experience under his belt. He graduated from IIT Kharagpur with a Bachelors and Masters degree in Mathematics and Computing. Since then, he has worked in organizations at varying stages of growth: from fast growing e-commerce startups like Meesho to behemoths like Adobe. He has drivennseveral pivotal features in every company he has worked in, like building an end-to-end recommendation system for the Meesho app, curating interesting advertising using Reinforcement Learning based optimizations in Adobe Advertising. He is currently working at Arista Networks, building AI driven apps responsible for cybersecurity of several Fortune 500 companies.

See other products by Subhajoy Das

Personalised recommendations for you

Based on your interests and search pattern

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m