Broadcast Date: May 30, 2019

Level: 300

Recommendation engines make use cases like targeted marketing campaigns, discovering relationships between individuals and products for identifying trends and classifying users, re-ranking items, or delivering personalized notifications, and more, possible. Setting up and handling these engines with traditional methods is often a highly resource consuming task, hard to maintain, and can lead to inaccurate results leading to low impact in your business. In this tech talk, we will explore how by relying on services like Amazon Personalize, it is possible to create and manage recommendation engines efficiently, letting you focus on the real value of the data for your business. Furthermore, we will discover how the deep learning techniques available have a direct impact on the bottom line of your business, by increasing the accuracy leading to higher engagement and click through in your applications. We will briefly review how this works in context and dive into some demonstrations.

Learning Objectives

  • Explore the challenges faced when working with recommendation engines and how to address those efficiently
  • Learn how Amazon Personalize allows you to create and manage powerful recommendation engines
  • Learn what deep learning techniques are available for improving recommendation engines accuracy and its impact in the bottom line of your business

Who Should Attend?

Data Scientists, Data Analysts, Application Developers, Business Decision Makers, IT Professionals


  • Antonio Rodriguez, Solutions Architect, AWS

Learn More

To learn more about the services featured in this talk, please visit:

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