Discovering hidden patterns in your content through unsupervised learning

Session Track
Beyond Drupal
Skill level

Recommendation systems are a big part of Online applications because they are related to understanding people. Few well-known implementations that we come across daily are while buying things on Amazon, watching movies on Netflix, browsing through photos on Instagram / Pinterest, Reading an article on Medium. Recommendation engines have pervaded every single aspect of our digital life, and they will continue to shape our lives in the future.  Content recommendations on web sites are a must nowadays to engage Users / Visitors / Customers spend more time on your site and consume more offerings.

This session plans to demystify Content Recommendations putting it in the context of Natural Language Processing (NLP) and Machine Learning, covering their implementations spanning use and complexity levels - with Similarity implementations. We will deep dive into the different ways of preparing the data that we already have in our Content Management System. The session will explain how to implement the Engine using an Unsupervised Machine Learning approach, integration with Drupal, and touch upon the Architectures.