Videos, Slides, Case Studies and other GraphAware related resources

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.

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