Amazon SageMaker

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, 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 across your organization to build, train, deploy, and manage models at scale.

Enable more people to innovate with ML

SageMaker for Business Analysts

Business analysts

Make ML predictions using a visual interface with SageMaker Canvas.

SageMaker for business analysts »
SageMaker for Data Scientists

Data scientists

Prepare data and build, train, and deploy models with SageMaker Studio.

SageMaker for data scientists »
SageMaker for MLOps Engineers

ML engineers

Deploy and manage models at scale with SageMaker MLOps.

SageMaker for ML engineers »

A wide breadth and depth of features for the ML lifecycle

Support for the leading ML frameworks, toolkits, and programming languages

Hugging Face

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


lower TCO


reduction in data labeling costs

Up to 50%

faster training through more efficient use of GPUs


inference overhead latency


compliance programs (PCI, HIPAA, SOC 1/2/3, FedRAMP, ISO, and more)

What's new

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

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Get started faster with a self-paced tutorial

Gain hands-on experience to prepare data and build, train, and deploy ML models

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Deploy solutions with SageMaker JumpStart

Pre-built ML solutions that you can deploy with just a few clicks

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