Step 2: Create a Jupyter notebook in the SageMaker notebook instance - Amazon SageMaker

Step 2: Create a Jupyter notebook in the SageMaker notebook instance

Important

Custom IAM policies that allow Amazon SageMaker Studio or Amazon SageMaker Studio Classic to create Amazon SageMaker resources must also grant permissions to add tags to those resources. The permission to add tags to resources is required because Studio and Studio Classic automatically tag any resources they create. If an IAM policy allows Studio and Studio Classic to create resources but does not allow tagging, "AccessDenied" errors can occur when trying to create resources. For more information, see Provide Permissions for Tagging SageMaker Resources.

AWS Managed Policies for Amazon SageMaker that give permissions to create SageMaker resources already include permissions to add tags while creating those resources.

To start scripting for training and deploying your model, create a Jupyter notebook in the SageMaker notebook instance. Using the Jupyter notebook, you can run machine learning (ML) experiments for training and inference while using SageMaker features and the AWS infrastructure.

To create a Jupyter notebook
Animated screenshot that shows how to create a Jupyter notebook in the SageMaker notebook instance.

  1. Open the notebook instance as follows:

    1. Sign in to the SageMaker console at https://console.aws.amazon.com/sagemaker/.

    2. On the Notebook instances page, open your notebook instance by choosing either:

      • Open JupyterLab for the JupyterLab interface

      • Open Jupyter for the classic Jupyter view

      Note

      If the notebook instance status shows Pending in the Status column, your notebook instance is still being created. The status will change to InService when the notebook instance is ready to use.

  2. Create a notebook as follows:

    • If you opened the notebook in the JupyterLab view, on the File menu, choose New, and then choose Notebook. For Select Kernel, choose conda_python3. This preinstalled environment includes the default Anaconda installation and Python 3.

    • If you opened the notebook in the classic Jupyter view, on the Files tab, choose New, and then choose conda_python3. This preinstalled environment includes the default Anaconda installation and Python 3.

  3. Save the notebooks as follows:

    • In the JupyterLab view, choose File, choose Save Notebook As..., and then rename the notebook.

    • In the Jupyter classic view, choose File, choose Save as..., and then rename the notebook.