AWS News Blog

Category: Amazon SageMaker

Amazon SageMaker Processing – Fully Managed Data Processing and Model Evaluation

Today, we’re extremely happy to launch Amazon SageMaker Processing, a new capability of Amazon SageMaker that lets you easily run your preprocessing, postprocessing and model evaluation workloads on fully managed infrastructure. Training an accurate machine learning (ML) model requires many different steps, but none is potentially more important than preprocessing your data set, e.g.: Converting […]

Amazon SageMaker Autopilot – Automatically Create High-Quality Machine Learning Models With Full Control And Visibility

Update September 30, 2021 – This post has been edited to remove broken links. Today, we’re extremely happy to launch Amazon SageMaker Autopilot to automatically create the best classification and regression machine learning models, while allowing full control and visibility. In 1959, Arthur Samuel defined machine learning as the ability for computers to learn without being […]

Amazon SageMaker Experiments – Organize, Track And Compare Your Machine Learning Trainings

Today, we’re extremely happy to announce Amazon SageMaker Experiments, a new capability of Amazon SageMaker that lets you organize, track, compare and evaluate machine learning (ML) experiments and model versions. ML is a highly iterative process. During the course of a single project, data scientists and ML engineers routinely train thousands of different models in […]

Now Available on Amazon SageMaker: The Deep Graph Library

Today, we’re happy to announce that the Deep Graph Library, an open source library built for easy implementation of graph neural networks, is now available on Amazon SageMaker. In recent years, Deep learning has taken the world by storm thanks to its uncanny ability to extract elaborate patterns from complex data, such as free-form text, […]

New for Amazon Aurora – Use Machine Learning Directly From Your Databases

March 23, 2020: Post updated to clarify networking, IAM permissions, and database configurations required to use machine learning from Aurora databases. A new notebook using SageMaker Autopilot gives a complete example, from the set up of the model to the creation of the SQL function using the endpoint. The integrations described in this post are now available for MySQL and […]

Now available in Amazon SageMaker: EC2 P3dn GPU Instances

In recent years, the meteoric rise of deep learning has made incredible applications possible, such as detecting skin cancer (SkinVision) and building autonomous vehicles (TuSimple). Thanks to neural networks, deep learning indeed has the uncanny ability to extract and model intricate patterns from vast amounts of unstructured data (e.g. images, video, and free-form text). However, […]

AWS Tech Talks

Learn about AWS Services & Solutions – September AWS Online Tech Talks

Learn about AWS Services & Solutions – September AWS Online Tech Talks Join us this September to learn about AWS services and solutions. The AWS Online Tech Talks are live, online presentations that cover a broad range of topics at varying technical levels. These tech talks, led by AWS solutions architects and engineers, feature technical […]

Managed Spot Training: Save Up to 90% On Your Amazon SageMaker Training Jobs

Amazon SageMaker is a fully-managed, modular machine learning (ML) service that enables developers and data scientists to easily build, train, and deploy models at any scale. With a choice of using built-in algorithms, bringing your own, or choosing from algorithms available in AWS Marketplace, it’s never been easier and faster to get ML models from […]