Amazon Personalize is a machine learning service that makes it easy for developers to create individualized recommendations for customers using their applications.

Machine learning is being increasingly used to improve customer engagement by powering personalized product and content recommendations, tailored search results, and targeted marketing promotions. However, developing the machine learning capabilities necessary to produce these sophisticated recommendation systems has been beyond the reach of most organizations today due to the complexity of developing machine learning functionality. Amazon Personalize allows developers with no prior machine learning experience to easily build sophisticated personalization capabilities into their applications, using machine learning technology perfected from years of use on Amazon.com.

This lab will walk you through the following:

  • Deploy and configure a Video Recommendation application
  • Setting up a Jupyter Notebook environment to interact with Amazon Personalize
  • Downloading and preparing training data, based on the Movie Lens dataset
  • Importing prepared data into Amazon Personalize
  • Building an ML model based upon the Hierarchical Recurrent Neural Network (HRNN) algorithm
  • Testing your model by deploying an Amazon Personalize campaign
  • Adding your campaign to the Video Recommendation application

A live demo of what we’ll be building today is available here: https://www.personalisevideorecs.info/recommend/