Amazon SageMaker Examples
A collection of example Jupyter notebooks demonstrating how to build, train and deploy machine learning models on Amazon SageMaker, maintained alongside the newer SageMaker-Core Python SDK.
This repository collects example Jupyter notebooks that demonstrate how to build, train and deploy machine learning models using Amazon SageMaker, maintained directly by the SageMaker team and covering the breadth of SageMaker's own features; a separate community repository holds additional examples and reference solutions.
It also introduces SageMaker-Core, a Python SDK offering an object-oriented interface to SageMaker resources such as training jobs, models and endpoints. SageMaker-Core adds resource chaining so objects can be passed as parameters instead of specified manually, abstracts low-level state transitions and polling, and adds code completion, documentation and type hints on top of the existing Boto3-based access.