Amazon SageMaker Example Notebooks
Welcome to Amazon SageMaker. This site highlights example Jupyter notebooks for a variety of machine learning use cases that you can run in SageMaker.
This site is based on the SageMaker Examples repository on GitHub. To run these notebooks, you will need a SageMaker Notebook Instance or SageMaker Studio. Refer to the SageMaker developer guide’s Get Started page to get one of these set up.
On a Notebook Instance, the examples are pre-installed and available from the examples menu item in JupyterLab. On SageMaker Studio, you will need to open a terminal, go to your home folder, then clone the repo with the following:
git clone https://github.com/aws/amazon-sagemaker-examples.git
We recommend the following notebooks as a broad introduction to the capabilities that SageMaker offers. To explore in even more depth, we provide additional notebooks covering even more use cases and frameworks.