Amazon SageMaker is one of the fastest growing services in the history of AWS, and today, tens of thousands of customers use SageMaker to build, train, and deploy high quality machine learning (ML) models. SageMaker brings together a broad set of capabilities purpose-built for ML including labeling, data preparation, feature engineering, statistical bias detection, auto-ML, training, tuning, hosting, explainability, monitoring, and workflows.
To help customers move faster on their ML projects, we are launching SageMaker Month where you can learn all about SageMaker including how to build, train, and deploy models faster. Take advantage of hands-on workshops, purpose-built tools, and getting started resources to improve team productivity by 10x. In addition, we are introducing several ways for you to save on SageMaker. First, you can save up to 64% using the new savings plans. Amazon SageMaker Savings Plans offer a flexible, usage-based pricing model in exchange for a commitment of consistent usage for a one or three year term. Plus, AWS reduced the price of several instance families by up to 14.2% so you can save even more.
Check out the SageMaker Month calendar to learn more.
April
Introducing the Amazon SageMaker Savings Plans, flexible plans to save up to 64% on ML usage costs
Machine learning for everyone with Domo and Amazon SageMaker Autopilot, bring together ML and BI
Learn how to use Amazon SageMaker Ground Truth to improve the quality of video annotations
Register to join the Amazon SageMaker fully-remote, day-long technical workshop
May
Learn how Genworth built a serverless ML pipeline on AWS using SageMaker
Profile infrastructure usage and cut costs with SageMaker Debugger
Build a dashboard of data labels with SageMaker Ground Truth
Get hands on building, training, and deploying models with SageMaker
How to use time travel with SageMaker Feature Store and experiment more quickly
Detect bias in ML models and understand model predictions
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