Category: Amazon SageMaker

Amazon SageMaker continues to iterate quickly and release new features on behalf of customers. Starting today, SageMaker adds support for many new instance types, local testing with the SDK, and Apache MXNet 1.1.0 and Tensorflow 1.6.0. Let’s take a quick look at each of these updates. New Instance Types Amazon SageMaker customers now have additional […]

Mid-march in the USA means millions of people watching, and betting on, college basketball (I live here but I didn’t make the rules). As the NCAA college championship continues I wanted to briefly highlight the work of Wesley Pasfield one of our Professional Services Machine Learning Specialists. Wesley was able to take data from kenpom.com […]

Kumar Venkateswar, Product Manager on the AWS ML Platforms Team, shares details on the announcement of Auto Scaling with Amazon SageMaker. With Amazon SageMaker, thousands of customers have been able to easily build, train and deploy their machine learning (ML) models. Today, we’re making it even easier to manage production ML models, with Auto Scaling […]

Machine Learning is a pivotal technology for many startups and enterprises. Despite decades of investment and improvements, the process of developing, training, and maintaining machine learning models has still been cumbersome and ad-hoc. The process of incorporating machine learning into an application often involves a team of experts tuning and tinkering for months with inconsistent […]