Amazon SageMaker JumpStart

Machine learning (ML) hub with foundation models, built-in algorithms, and prebuilt ML solutions that you can deploy with just a few clicks

Why SageMaker JumpStart?

Amazon SageMaker JumpStart is a machine learning (ML) hub that can help you accelerate your ML journey. With SageMaker JumpStart, you can evaluate, compare, and select FMs quickly based on pre-defined quality and responsibility metrics to perform tasks like article summarization and image generation. Pretrained models are fully customizable for your use case with your data, and you can easily deploy them into production with the user interface or SDK. In addition, you can access prebuilt solutions to solve common use cases, and share ML artifacts, including ML models and notebooks, within your organization to accelerate ML model building and deployment.

None of your data is used to train the underlying models. Since all data is encrypted and does not leave your virtual private cloud (VPC), you can trust that your data will remain private and confidential. See FAQs for more information.

How it works

  • Foundation models
  • Built-in algorithms with pretrained models
  • Solutions
  • Solutions how it works diagram
  • ML artifact sharing
  • ML artifact sharing HIW diagram

Benefits of SageMaker JumpStart

Publicly available foundation models

Foundation models from popular model providers for text and image generation that are fully customizable

Built-in ML algorithms

Hundreds of built-in algorithms with pretrained models from popular model hubs

Customizable solutions

Fully customizable solutions for common use cases with reference architectures to accelerate your ML journey

Support collaboration

Share ML models and notebooks across your organization to accelerate ML model building and deployment

Amazon SageMaker JumpStart features

Foundation Models

Explore numerous proprietary and publicly available foundation models to perform a wide range of tasks such as article summarization and text, image, or video generation.

Access hundreds of built-in algorithms

SageMaker JumpStart provides hundreds of built-in algorithms with pretrained models from model hubs. You can also access built-in algorithms using the SageMaker Python SDK. Built-in algorithms cover common ML tasks, such as data classifications (image, text, tabular) and sentiment analysis.

Prebuilt solutions for common use cases

SageMaker JumpStart provides one-click, end-to-end solutions for many common machine learning use cases such as demand forecasting, credit rate prediction, fraud detection and computer vision.

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