Generate batch personalized recommendations using Amazon Personalize
-
Updated
Nov 18, 2020 - Jupyter Notebook
Generate batch personalized recommendations using Amazon Personalize
The Maintaining Personalized Experiences with Machine Learning solution provides an automated pipeline to maintain resources in Amazon Personalize. This pipeline allows you to keep up to date with your user’s most recent activity while sustaining and improving the relevance of recommendations
Automatic (periodic) retraining of Amazon Personalize
An example using Amazon Personalize to generate recommendations for a fictional online store
Customized Amazon Personalize PoC-in-a-Box materials
Create higher-quality recommendations in your e-Commerce platform
Pipeline for data ingestion to Amazon Personalize and user interaction history tracking
An Amazon Personalize based recommendation engine reference implementation to provide you a fast kickstart.
Amazon Personalize (Machine Learning / Artificial Intelligence)
Amazon Personalize Langchain extensions to support invoking and retrieving personalized recommendations from your Amazon Personalize resources
DRAFT demo of past-interaction-based call routing with Amazon Connect and Amazon Personalize
Rotates Amazon Personalize filters on a schedule based on dynamic templates
Add a description, image, and links to the amazon-personalize topic page so that developers can more easily learn about it.
To associate your repository with the amazon-personalize topic, visit your repo's landing page and select "manage topics."