Amazon SageMaker AI
- Category
- AWS services
- Docs outline
- 12 sections
Official docs outline
docs.aws.amazon.com- What is SageMaker AI
Managed ML platform covering data prep, training, deployment and monitoring.
- Machine learning environments
Studio, notebook instances and other development environments.
- Prepare data
Data labeling, Data Wrangler and processing for ML datasets.
- Feature Store
Online and offline stores for reusable ML features.
- Model training
Training jobs, built-in algorithms, distributed training and managed spot training.
- JumpStart
Pretrained models and solution templates.
- Model customization
Fine-tuning foundation models.
- Deploy models for inference
Real-time, serverless, asynchronous and batch inference endpoints.
- MLOps and pipelines
Pipelines, model registry and CI/CD for ML.
- Model Registry
Versioning and approving models for deployment.
- Model monitoring
Detecting data and model quality drift.
- Security
IAM, VPC and encryption for SageMaker resources.
Each section links to the official page. Titles and summaries by Extra Credit; the docs belong to their authors.