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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 and Preprocess Data.

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

To create an Amazon SageMaker notebook instance

1. Open the Amazon SageMaker console at https://console.aws.amazon.com/sagemaker/.

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.

   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.

Step 3: Create a Jupyter Notebook.