Step 2: Create a Jupyter Notebook

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

To create a Jupyter notebook

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 or 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 for 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.