Build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows
Enable more people to innovate with ML through a choice of tools—IDEs for data scientists and no-code interface for business analysts.
Access, label, and process large amounts of structured data (tabular data) and unstructured data (photo, video, geospatial, and audio) for ML.
Reduce training time from hours to minutes with optimized infrastructure. Boost team productivity up to 10 times with purpose-built tools.
Automate and standardize MLOps practices and governance across your organization to support transparency and auditability.
Enable more people to innovate with ML
Make ML predictions using a visual interface with SageMaker Canvas.
Prepare data and build, train, and deploy models with SageMaker Studio.
Deploy and manage models at scale with SageMaker MLOps.
Support for the leading ML frameworks, toolkits, and programming languages
High-performance, low-cost ML at scale
Amazon SageMaker is built on Amazon’s two decades of experience developing real-world ML applications, including product recommendations, personalization, intelligent shopping, robotics, and voice-assisted devices.
increase in team productivity
predictions per month
Up to 50%
Amazon SageMaker is used by tens of thousands of customers across a wide range of industries.
What’s New announcements are high-level summaries of launches and feature updates. Read Amazon SageMaker specific updates.
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Learn ML with SageMaker Studio Lab
Learn and experiment with ML using a no-setup, free development environment
Get started faster with a self-paced tutorial
Gain hands-on experience to prepare data and build, train, and deploy ML models
Deploy solutions with SageMaker JumpStart
Pre-built ML solutions that you can deploy with just a few clicks