Author: Luis Lopez Soria

Today, we’re excited to announce a new similar items recommendation recipe (aws-similar-items) in Amazon Personalize that helps you leverage your users’ interaction histories and what you know about the items in your catalog to deliver relevant recommendations. Across Amazon, we provide personalized experiences for each of our users, and based on a user’s interests, we […]

This is a guest post by Shae Selix (Staff Data Scientist at Calm) and Luis Lopez Soria (Sr. AI/ML Specialist SA at AWS). Today, content is proliferating. It’s being produced in many different forms by a host of content providers, both large and small. Whether it’s on-demand video, music, podcasts, or other forms of rich […]

Machine learning (ML)-based recommender systems aren’t a new concept, but developing such a system can be a resource-intensive task—from data management during training and inference, to managing scalable real-time ML-based API endpoints. Amazon Personalize allows you to easily add sophisticated personalization capabilities to your applications by using the same ML technology used on Amazon.com for […]

Getting relevant recommendations in front of your users at the right time is a crucial step for the success of your personalization strategy. However, your customer’s decision-making process shifts depending on the context at the time when they’re interacting with your recommendations. In this post, I show you how to set up and query a […]

May 2023: Please refer to Automate the deployment of an Amazon Forecast time-series forecasting model blog post for latest practices on forecasting automation. This post demonstrates how to create a serverless Machine Learning Operations (MLOps) pipeline to develop and visualize a forecasting model built with Amazon Forecast. Because Machine Learning (ML) workloads need to scale, […]