# Amazon SageMaker AI Documentation

Amazon SageMaker AI is a fully managed machine learning service. With Amazon SageMaker AI, data scientists and developers can quickly build and train machine learning models, and then deploy them into a production-ready hosted environment.

## Automation and Environments

- [Get Started](/sagemaker/latest/dg/gs.html?icmpid=docs_sagemaker_lp): Onboard to the Amazon SageMaker AI role and domain.
- [Use Automated ML](/sagemaker/latest/dg/use-auto-ml.html?icmpid=docs_sagemaker_lp): Learn how to automate machine learning from start to finish.
- [Use Machine Learning Environments](/sagemaker/latest/dg/machine-learning-environments.html): Learn about machine learning environments that Amazon SageMaker AI offers.

## Work with Data

- [Label Data with a Human-in-the-loop](/sagemaker/latest/dg/data-label.html): Learn how to use a human-in-the-loop to help label data more accurately.
- [Prepare Data](/sagemaker/latest/dg/data-prep.html): Learn how to prepare data for machine learning.
- [Process Data](/sagemaker/latest/dg/processing-job.html): Learn how to process data for machine learning.
- [Create, Store, and Share Features](/sagemaker/latest/dg/feature-store.html): Learn how to create, store, and share extracted data signals (features) for machine learning.

## Work with Models

- [Train Models](/sagemaker/latest/dg/train-model.html): Learn how to train your machine learning models.
- [Deploy Models for Inference](/sagemaker/latest/dg/deploy-model.html): Learn how to deploy your machine learning models for inference.
- [Implement MLOps](/sagemaker/latest/dg/mlops.html): Learn how to implement machine learning operations on Amazon SageMaker AI.
- [Monitor Data and Model Quality](/sagemaker/latest/dg/model-monitor.html): Learn how to monitor data and model quality.
- [Use Docker Containers to Build Models](/sagemaker/latest/dg/docker-containers.html): Learn how to use Docker containers to build your machine learning models.

## Responsible AI

- [Detect Bias and Understand Explanations](/sagemaker/latest/dg/model-explainability.html): Learn how to detect bias and understand explanations in machine learning models.
- [Use Governance](/sagemaker/latest/dg/governance.html): Learn how to use governance to document and track model performance.
- [Configure Security in Amazon SageMaker AI](/sagemaker/latest/dg/security.html): Learn how to secure resources in Amazon SageMaker AI.

## Reference

- [API Reference](/sagemaker/latest/APIReference/Welcome.html?icmpid=docs_sagemaker_lp): Describes all of the API operations for Amazon SageMaker AI in detail.
- [Amazon SageMaker AI Python SDK](https://sagemaker.readthedocs.io/en/stable/index.html): Use the Amazon SageMaker AI Python SDK library to train and deploy models using popular deep learning frameworks and algorithms.
- [AWS SDK for Python (Boto3)](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html?icmpid=docs_sagemaker_lp): Use the AWS SDK for Python (Boto3) to format model data and build applications to build, train, and deploy machine learning models.

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## Get Started

- [Create, Train, and Deploy a Simple Machine Learning Model](https://docs.aws.amazon.com/sagemaker/latest/dg/gs.html?icmpid=docs_sagemaker_lp)
- [AWS Quick Start - Predictive Data Science with Amazon SageMaker and a Data Lake on AWS](https://aws.amazon.com/quickstart/architecture/predictive-data-science-sagemaker-and-data-lake/?icmpid=docs_sagemaker_lp)

## Related Info

- [Product Information](https://aws.amazon.com/sagemaker/?icmpid=docs_sagemaker_lp)
- [Pricing](https://aws.amazon.com/sagemaker/pricing/?icmpid=docs_sagemaker_lp)
- [FAQs](https://aws.amazon.com/sagemaker/faqs/?icmpid=docs_sagemaker_lp)
- [AWS Machine Learning Blog](https://aws.amazon.com/blogs/machine-learning/?icmpid=docs_sagemaker_lp)
- [Amazon SageMaker Forum](https://forums.aws.amazon.com/forum.jspa?forumID=285)
- [SDKs & Tools](https://aws.amazon.com/tools/)
- [AWS General Reference](/general/latest/gr/Welcome.html?icmpid=docs_sagemaker_lp)
- [AWS Training](https://aws.amazon.com/training/learning-paths/machine-learning/?icmpid=docs_sagemaker_lp)
- [Machine Learning Customers and Case Studies](https://aws.amazon.com/machine-learning/customers/?icmpid=docs_sagemaker_lp)
- [AWS Whitepapers](https://aws.amazon.com/whitepapers/?icmpid=docs_sagemaker_lp#machine-learning)
- [Contact Us](https://aws.amazon.com/contact-us/?icmpid=docs_sagemaker_lp)