Resources - graphs

Videos, Slides, Case Studies and other GraphAware related resources

Graph-Powered Machine Learning Q&A

17 Nov 2021 videos graphs ML

An introduction to Graph-Powered Machine Learning written by our very own Dr. Alessandro Negro. This book is an extraction of 60 combined years of experience in graphs, and explains how graphs and graph databases can serve machine learning projects.

Unparalleled Graph Database Scalability Delivered by Neo4j 4.0 - Graph Powered Machine Learning

04 Apr 2020 slides Neo4j ML graphs

Presentation by Dr. Alessandro Negro, Chief Scientist at GraphAware and author of the Manning’s book Graph-powered machine learning, that covers the following topics:

Why unlimited scale is important when using graph databases

The new graph database scaling capabilities built by Neo4j developers

The role of graphs to support machine learning application

How Neo4j assists customers in scaling their applications

Concrete examples of machine learning projects that can leverage graph sharding

The recording is available as well:

Graph-Powered Machine Learning - Book

10 Jan 2020 publications ML graphs

At its core, machine learning is about efficiently identifying patterns and relationships in data. Many tasks, such as finding associations among terms so you can make accurate search recommendations or locating individuals within a social network who have similar interests, are naturally expressed as graphs. Graph-Powered Machine Learning teaches you how to use graph-based algorithms and data organization strategies to develop superior machine learning applications.

Get the book

Fix your microservice architecture using graph analysis - full video

10 Oct 2019 videos microservices graphs analytics

To improve the performance of your microservice architecture, you may consider using graph analysis techniques. By using tools like jQAssistant and Neo4j, you can identify potential issues, better understand the relationships between different services, and even analyze the potential impact of changes on your system. With these tools, you can answer questions like:

Are there any antipatterns present in my microservice architecture? How will certain database refactoring efforts affect the other services in my system? Is my API documentation and specification accurate and up to date? Can I get a clear and current visualization of my entire system?

By implementing graph analysis techniques, you can work towards optimizing the design and functionality of your microservice architecture.

Lean Dependency Management with graphs

12 Feb 2019 slides graphs

Unblocking dependencies benefits any organization that performs work concurrently. Dependencies are connected and modelling them as a graph surfaces those connections quickly, enabling decisions to be taken that promote zero waste and more efficient delivery.