Amazon SageMaker

Amazon SageMaker is a fully managed machine learning (ML) service. With SageMaker, data scientists and developers can quickly and confidently build, train, and deploy ML models into a production-ready hosted environment. It provides a UI experience for running ML workflows that makes SageMaker ML tools available across multiple integrated development environments (IDEs).

With SageMaker, you can store and share your data without having to build and manage your own servers. This gives you or your organizations more time to collaboratively build and develop your ML workflow, and do it sooner. SageMaker provides managed ML algorithms to run efficiently against extremely large data in a distributed environment. With built-in support for bring-your-own-algorithms and frameworks, SageMaker offers flexible distributed training options that adjust to your specific workflows. Within a few steps, you can deploy a model into a secure and scalable environment from the SageMaker console.

Use automated ML, no-code, or low-code

Amazon SageMaker offers the following features to automate key machine learning tasks and use no-code or low-code solutions.

Amazon SageMaker Autopilot is an automated machine learning (AutoML) feature-set that automates the end-to-end process of building, training, tuning, and deploying machine learning models. Amazon SageMaker Autopilot analyzes your data, selects algorithms suitable for your problem type, preprocesses the data to prepare it for training, handles automatic model training, and performs hyperparameter optimization to find the best performing model for your dataset.

SageMaker JumpStart provides pretrained, open-source models for a wide range of problem types to help you get started with machine learning. You can incrementally train and tune these models before deployment. JumpStart also provides solution templates that set up infrastructure for common use cases, and executable example notebooks for machine learning with SageMaker.

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SageMaker Autopilot⁠

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SageMaker JumpStart⁠

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