Step 2: Create an Amazon SageMaker Notebook Instance - Amazon SageMaker

Step 2: Create an Amazon SageMaker Notebook Instance

An Amazon SageMaker notebook instance is a fully managed machine learning (ML) Amazon Elastic Compute Cloud (Amazon EC2) compute instance that runs the Jupyter Notebook App. You use the notebook instance to create and manage Jupyter notebooks that you can use to prepare and process data and to train and deploy machine learning models. For more information, see Explore, Analyze, and Process Data.


If necessary, you can change the notebook instance settings, including the ML compute instance type, later.

To create a SageMaker notebook instance

  1. Open the Amazon SageMaker console at

  2. Choose Notebook instances, then choose Create notebook instance.

  3. On the Create notebook instance page, provide the following information (if a field is not mentioned, leave the default values):

    1. For Notebook instance name, type a name for your notebook instance.

    2. For Instance type, choose ml.t2.medium. This is the least expensive instance type that notebook instances support, and it suffices for this exercise. If a ml.t2.medium instance type isn't available in your AWS Region, choose ml.t3.medium.

    3. For IAM role, choose Create a new role, then choose Create role.

    4. Choose Create notebook instance.

      In a few minutes, Amazon SageMaker launches an ML compute instance—in this case, a notebook instance—and attaches an ML storage volume to it. The notebook instance has a preconfigured Jupyter notebook server and a set of Anaconda libraries.

Next Step

Step 3: Create a Jupyter Notebook.