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.

SageMaker Savings Plan Overview (11:04) 

April

Tuesday, 20th
Amazon SageMaker Month - April 20

Introducing the Amazon SageMaker Savings Plans, flexible plans to save up to 64% on ML usage costs

Read the blog »
Tuesday, 20th
Amazon SageMaker Month - April 20

Machine learning for everyone with Domo and Amazon SageMaker Autopilot, bring together ML and BI

Read the blog »
Thursday, 22nd
Amazon SageMaker Month - April 22

Learn how to use Amazon SageMaker Ground Truth to improve the quality of video annotations

Read the blog >>
Friday, 23rd
Amazon SageMaker Month - April 23

Register to join the Amazon SageMaker fully-remote, day-long technical workshop

Explore the workshop »
Monday, 26th
Amazon SageMaker Month - April 26

Easily prepare data for ML with Amazon SageMaker Data Wrangler

Read the blog >>
Tuesday, 27th
Amazon SageMaker Month - April 27

Build analytics in Tableau using models deployed on SageMaker

Join the tech talk »
Tuesday, 27th
Amazon SageMaker Month - April 27

Manage and monitor models on edge devices such as wind turbines

Read the blog >>
Tuesday, 27th
Amazon SageMaker Month - April 27

Step-by-step guide to building predictive analytics

Get the playbook >>
Thursday, 29th
Amazon SageMaker Month - April 29

Annotate point cloud data using Amazon SageMaker Ground Truth

Read the blog >>
Friday, 30th
Amazon SageMaker Month - April 30

Meet one of LinkedIn's top AI voices, Greg Coquillo

Sign up »

May

Monday, 3rd
Amazon SageMaker Month - May 3

Train and tune high quality deep learning models using SageMaker

Read the blog >>
Wednesday, 5th
Amazon SageMaker Month - May 4

Automate data labeling workflows with SageMaker Ground Truth

Read the blog >>
Thursday, 6th
Amazon SageMaker Month - May 6

Deploy and manage models over time at scale with SageMaker

Read the blog >>
Friday, 7th
Amazon SageMaker Month - May 7

Tips for managing and customizing SageMaker Studio Notebooks

Read the blog >>
Friday, 7th
Amazon SageMaker Month - May 7

Learn how Genworth built a serverless ML pipeline on AWS using SageMaker

Read the blog >>
Wednesday, 12th
Amazon SageMaker Month - May 12

Get hands on building, training, and deploying models with SageMaker

Explore the workshop >>
Thursday, 13th
Amazon SageMaker Month - May 13

Build a dashboard of data labels with SageMaker Ground Truth

Read the blog >>
Friday, 14th
Amazon SageMaker Month - May 14

Prepare data for predicting credit risk using SageMaker Data Wrangler and Clarify

Read the blog >>
Tuesday, 18th
Amazon SageMaker Month - May 18

Speed up YOLOv4 inference by 2x on SageMaker

Read the blog >>
Friday, 21th
Amazon SageMaker Month - May 21
Optimize SageMaker inference in the cloud
Read the blog >>
Friday, 21st
Amazon SageMaker Month - May 21

It's a wrap, summary of SageMaker announcements

Read the blog >>
AWS Heroes

AWS Machine Learning Heroes

Learn more about Amazon SageMaker from the community
Learn more