<p><iframe allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen="" frameborder="0" height="315" src="https://www.youtube.com/embed/an-2SEOCxaw" width="560"></iframe></p>

<p>This talk covers fundamentals of recommendation systems and how to build one using DataStax Enterprise Graph. We discuss content-based, collaborative filtering and hybrid approaches to predictive modeling as well as possible design patterns for a real-time recommender service. Using DataStax Studio, we will walk through several examples of Gremlin recommender traversals, demonstrate how they work, and discuss their advantages and limitations.</p>


Artem Chebotko

https://www.youtube.com/watch?v=an-2SEOCxaw&feature=youtu.be

Building a Recommendation System with DataStax Enterprise Graph

Speakers

Artem Chebotko

Open-Source, Scale-Out, Cloud-Native Cassandra-as-a-Service

Data Modeling in Apache Cassandra™

Cassandra: The Definitive Guide - 3rd Edition | O'Reilly

Building a Recommendation System with DataStax Enterprise Graph

Speakers

Artem Chebotko

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Open-Source, Scale-Out, Cloud-Native Cassandra-as-a-Service

Data Modeling in Apache Cassandra™

Cassandra: The Definitive Guide - 3rd Edition | O'Reilly