0

Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Graph Machine Learning

You're reading from Graph Machine Learning Take graph data to the next level by applying machine learning techniques and algorithms

Product type Paperback

Published in Jun 2021

Publisher Packt

ISBN-13 9781800204492

Length 338 pages

Edition 1st Edition

Languages

Python

Concepts

Machine Learning

Authors (3):

Aldo Marzullo

Claudio Stamile

Enrico Deusebio

View More author details

Table of Contents (15) Chapters

Preface

1. Section 1 – Introduction to Graph Machine Learning

2. Chapter 1: Getting Started with Graphs FREE CHAPTER

3. Chapter 2: Graph Machine Learning

4. Section 2 – Machine Learning on Graphs

5. Chapter 3: Unsupervised Graph Learning

6. Chapter 4: Supervised Graph Learning

7. Chapter 5: Problems with Machine Learning on Graphs

8. Section 3 – Advanced Applications of Graph Machine Learning

9. Chapter 6: Social Network Graphs

10. Chapter 7: Text Analytics and Natural Language Processing Using Graphs

11. Chapter 8:Graph Analysis for Credit Card Transactions

12. Chapter 9: Building a Data-Driven Graph-Powered Application

13. Chapter 10: Novel Trends on Graphs

14. Other Books You May Enjoy

Summary

In this section, we have provided you with the basic concepts of how to design, implement, and deploy data-driven applications that resort to graph modeling and leverage graph structures. We have highlighted the importance of a modular approach, which is usually the key to seamlessly scaling any data-driven use case from early-stage MVPs to production systems that can handle a large amount of data and large computational performances.

We have outlined the main architectural pattern, which should provide you with a guide when designing the backbone structure of your data-driven applications. We then continued by describing the main components that are the basis of graph-powered applications: graph processing engines, graph databases, and graph querying languages. For each component, we have provided an overview of the most common tools and libraries, with practical examples that will help you to build and implement your solutions. You should thus have by now a good overview...

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 (3)

Claudio Stamile

Claudio Stamile

Claudio Stamile received an M.Sc. degree in computer science from the University of Calabria (Cosenza, Italy) in September 2013 and, in September 2017, he received his joint Ph.D. from KU Leuven (Leuven, Belgium) and Université Claude Bernard Lyon 1 (Lyon, France). During his career, he has developed a solid background in artificial intelligence, graph theory, and machine learning, with a focus on the biomedical field. He is currently a senior data scientist in CGnal, a consulting firm fully committed to helping its top-tier clients implement data-driven strategies and build AI-powered solutions to promote efficiency and support new business models.

See other products by Claudio Stamile

Enrico Deusebio

Enrico Deusebio

Enrico Deusebio is currently the chief operating officer at CGnal, a consulting firm that helps its top-tier clients implement data-driven strategies and build AI-powered solutions. He has been working with data and large-scale simulations using high-performance facilities and large-scale computing centers for over 10 years, both in an academic and industrial context. He has collaborated and worked with top-tier universities, such as the University of Cambridge, the University of Turin, and the Royal Institute of Technology (KTH) in Stockholm, where he obtained a Ph.D. in 2014. He also holds B.Sc. and M.Sc. degrees in aerospace engineering from Politecnico di Torino.

See other products by Enrico Deusebio

Aldo Marzullo

Aldo Marzullo

Aldo Marzullo received an M.Sc. degree in computer science from the University of Calabria (Cosenza, Italy) in September 2016. During his studies, he developed a solid background in several areas, including algorithm design, graph theory, and machine learning. In January 2020, he received his joint Ph.D. from the University of Calabria and Université Claude Bernard Lyon 1 (Lyon, France), with a thesis entitled Deep Learning and Graph Theory for Brain Connectivity Analysis in Multiple Sclerosis. He is currently a postdoctoral researcher at the University of Calabria and collaborates with several international institutions.

See other products by Aldo Marzullo

Other recommended products

Related to this chapter

Network Science with Python and NetworkX Quick Start Guide

Network Science with Python and NetworkX Quick Start Guide

The emerging field of Network Science is about understanding different kind of relationships. This book covers the latest version 2.x of NetworkX for performing Network Science with Python.You will also learn the fundamentals of network theory and see practical examples of how they are applied to real-world problems using Python and NetworkX.

Apr 2019 6h 20m

Network Science with Python and NetworkX Quick Start Guide

Network Science with Python and NetworkX Quick Start Guide

The emerging field of Network Science is about understanding different kind of relationships. This book covers the latest version 2.x of NetworkX for performing Network Science with Python.You will also learn the fundamentals of network theory and see practical examples of how they are applied to real-world problems using Python and NetworkX.

Apr 2019 6h 20m

Network Science with Python and NetworkX Quick Start Guide

Network Science with Python and NetworkX Quick Start Guide

The emerging field of Network Science is about understanding different kind of relationships. This book covers the latest version 2.x of NetworkX for performing Network Science with Python.You will also learn the fundamentals of network theory and see practical examples of how they are applied to real-world problems using Python and NetworkX.

Apr 2019 6h 20m

Hands-On Graph Analytics with Neo4j

Hands-On Graph Analytics with Neo4j

To start with you will cover the basics of graph analytics, Cypher querying language, components of graph architecture, and more. You will implement Neo4j techniques to understand various graph analytics methods to reveal complex relationships in data. You will understand how machine learning can be used to perform smarter graph analytics.

Aug 2020 17h 0m

Hands-On Graph Analytics with Neo4j

Hands-On Graph Analytics with Neo4j

To start with you will cover the basics of graph analytics, Cypher querying language, components of graph architecture, and more. You will implement Neo4j techniques to understand various graph analytics methods to reveal complex relationships in data. You will understand how machine learning can be used to perform smarter graph analytics.

Aug 2020 17h 0m

Hands-On Graph Analytics with Neo4j

Hands-On Graph Analytics with Neo4j

To start with you will cover the basics of graph analytics, Cypher querying language, components of graph architecture, and more. You will implement Neo4j techniques to understand various graph analytics methods to reveal complex relationships in data. You will understand how machine learning can be used to perform smarter graph analytics.

Aug 2020 17h 0m

Hands-On Graph Analytics with Neo4j

Hands-On Graph Analytics with Neo4j

To start with you will cover the basics of graph analytics, Cypher querying language, components of graph architecture, and more. You will implement Neo4j techniques to understand various graph analytics methods to reveal complex relationships in data. You will understand how machine learning can be used to perform smarter graph analytics.

Aug 2020 17h 0m

Hands-On Graph Analytics with Neo4j

Hands-On Graph Analytics with Neo4j

To start with you will cover the basics of graph analytics, Cypher querying language, components of graph architecture, and more. You will implement Neo4j techniques to understand various graph analytics methods to reveal complex relationships in data. You will understand how machine learning can be used to perform smarter graph analytics.

Aug 2020 17h 0m

Hands-On Graph Analytics with Neo4j

Hands-On Graph Analytics with Neo4j

To start with you will cover the basics of graph analytics, Cypher querying language, components of graph architecture, and more. You will implement Neo4j techniques to understand various graph analytics methods to reveal complex relationships in data. You will understand how machine learning can be used to perform smarter graph analytics.

Aug 2020 17h 0m

Hands-On Graph Analytics with Neo4j

Hands-On Graph Analytics with Neo4j

To start with you will cover the basics of graph analytics, Cypher querying language, components of graph architecture, and more. You will implement Neo4j techniques to understand various graph analytics methods to reveal complex relationships in data. You will understand how machine learning can be used to perform smarter graph analytics.

Aug 2020 17h 0m

Hands-On Graph Analytics with Neo4j

Hands-On Graph Analytics with Neo4j

To start with you will cover the basics of graph analytics, Cypher querying language, components of graph architecture, and more. You will implement Neo4j techniques to understand various graph analytics methods to reveal complex relationships in data. You will understand how machine learning can be used to perform smarter graph analytics.

Aug 2020 17h 0m

Hands-On Graph Analytics with Neo4j

Hands-On Graph Analytics with Neo4j

To start with you will cover the basics of graph analytics, Cypher querying language, components of graph architecture, and more. You will implement Neo4j techniques to understand various graph analytics methods to reveal complex relationships in data. You will understand how machine learning can be used to perform smarter graph analytics.

Aug 2020 17h 0m

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

Data Governance Handbook

Data Governance Handbook

This book provides a highly focused view of real business outcomes powered by data governance, that resonate with non-data executives such as CFOs and CEOs. You'll also find useful insights into how to implement data governance initiatives.

May 2024 13h 8m

Data Engineering with Databricks Cookbook

Data Engineering with Databricks Cookbook

This book shows you how to use Apache Spark, Delta Lake, and Databricks to build data pipelines, manage and transform data, optimize performance, and more. Additionally, you'll implement DataOps and DevOps practices, and orchestrate data workflows.

May 2024 14h 36m

Azure Data Engineer Associate Certification Guide

Azure Data Engineer Associate Certification Guide

Unlock the power of Azure data engineering with this certification guide, elevating your skills in data processing, storage, and security with the help of practical insights, hands-on exercises, and the latest advancements.

May 2024 18h 16m

Microsoft Power BI Cookbook

Microsoft Power BI Cookbook

Microsoft Power BI is the most sought-after platform for BI professionals' visualization needs. Explore the latest Power BI features, future AI enhancements, and integration with other Power Platform tools via new recipes in this updated edition.

Jul 2024 19h 56m

Python Data Cleaning Cookbook

Python Data Cleaning Cookbook

The book shows you how to clean, wrangle, and view data from multiple perspectives, including dataset and column attributes. You will cover common and not-so-common challenges that are faced while cleaning messy data for complex situations and learn to manipulate data to get it down to a form that can be useful for making the right decisions.

May 2024 16h 12m

Microsoft Azure AI Fundamentals AI-900 Exam Guide

Microsoft Azure AI Fundamentals AI-900 Exam Guide

This AI-900 study guide will help you prepare and practice for the certification exam. You'll delve into AI workloads, ML principles, computer vision, NLP, knowledge mining, and generative AI using Azure cloud services.

May 2024 9h 36m

Using Stable Diffusion with Python

Using Stable Diffusion with Python

This book shows you how to use Python to control Stable Diffusion and generate high-quality images. In addition to covering the basic usage of the diffusers package, the book provides solutions for extending the package for more advanced purposes.

Jun 2024 11h 44m

Getting Started with DuckDB

Getting Started with DuckDB

This hands-on book teaches you to analyze large datasets with blazing speed and ease. You will learn how to use DuckDB to quickly load, query, transform, analyze, and visualize data effectively through a series of practical examples.

Jun 2024 12h 44m

Databricks Certified Associate Developer for Apache Spark Using Python

Databricks Certified Associate Developer for Apache Spark Using Python

This guide gets you ready for certification with expert-backed content, key exam concepts, and topic reviews. Additionally, you'll be able to make the most of Apache Spark 3.0 to modernize workloads and more using specific tools and techniques.