AWS News Blog

Category: SageMaker

Amazon SageMaker Automatic Model Tuning: Using Machine Learning for Machine Learning

Today I’m excited to announce the general availability of Amazon SageMaker Automatic Model Tuning. Automatic Model Tuning eliminates the undifferentiated heavy lifting required to search the hyperparameter space for more accurate models. This feature allows developers and data scientists to save significant time and effort in training and tuning their machine learning models. A Hyperparameter […]

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Amazon SageMaker Updates – Tokyo Region, CloudFormation, Chainer, and GreenGrass ML

Today, at the AWS Summit in Tokyo we announced a number of updates and new features for . Starting today, SageMaker is available in ! SageMaker also now supports CloudFormation. A new machine learning framework, Chainer, is now available in the SageMaker Python SDK, in addition to MXNet and Tensorflow. Finally, support for running Chainer […]

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New – Machine Learning Inference at the Edge Using AWS Greengrass

What happens when you combine the Internet of Things, Machine Learning, and Edge Computing? Before I tell you, let’s review each one and discuss what AWS has to offer. Internet of Things (IoT) – Devices that connect the physical world and the digital one. The devices, often equipped with one or more types of sensors, […]

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Amazon SageMaker Now Supports Additional Instance Types, Local Mode, Open Sourced Containers, MXNet and Tensorflow Updates

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 […]

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March Machine Learning Madness!

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 […]

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Auto Scaling is now available for Amazon SageMaker

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 […]

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Amazon SageMaker – Accelerating Machine Learning

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 […]

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