CDK Corner – January 2021

December was an exciting month for CDK! Jason Fulghum delivered an AWS re:Invent presentation on how CDK has changed over the past year and what customers can expect in the next year. The highlight of this talk was the alpha release of CDK v2. This is the first major version Read more…

Automating Amazon Personalize solution using the AWS Step Functions Data Science SDK

Machine learning (ML)-based recommender systems aren’t a new concept across organizations such as retail, media and entertainment, and education, but developing such a system can be a resource-intensive task—from data labelling, training and inference, to scaling. You also need to apply continuous integration, continuous deployment, and continuous training to your Read more…

How to train procedurally generated game-like environments at scale with Amazon SageMaker RL

A gym is a toolkit for developing and comparing reinforcement learning algorithms. Procgen Benchmark is a suite of 16 procedurally-generated gym environments designed to benchmark both sample efficiency and generalization in reinforcement learning.  These environments are associated with the paper Leveraging Procedural Generation to Benchmark Reinforcement Learning (citation). Compared to Read more…

Automating Recommendation Engine Training with Amazon Personalize and AWS Glue

Customers from startups to enterprises observe increased revenue when personalizing customer interactions. Still, many companies are not yet leveraging the power of personalization, or, are relying solely on rule-based strategies. Those strategies are effort-intensive to maintain and not effective. Common reasons for not launching machine learning (ML) based personalization projects Read more…