Using Amazon SageMaker

In this section, we will demonstrate setting up an Amazon SageMaker notebook instance. Run a sample machine learning job and create an endpoint to host the model.

Note

Refer to the detailed comments and explanations in the sample Python notebook used in this section at: https://github.com/awslabs/amazon-sagemaker-examples/blob/master/introduction_to_applying_machine_learning/breast_cancer_prediction/Breast%20Cancer%20Prediction.ipynb.

1. Log in to AWS Management Console and go to the Amazon SageMaker console. Click on the Create notebook instance button:

2. On the Notebook instance settings, we will create an Amazon SageMaker execution role. Click on the IAM role drop-down list and select the Create a new role option:

3. Select the Any S3 bucket option and click on the Create role button:

4. Specify the Notebook instance name (as SageMakerTestNotebookInstance), select the Notebook Instance type, and select the No VPC option. Click on the Create notebook instance button: 

5. After the notebook...