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.
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.
- Log in to AWS Management Console and go to the Amazon SageMaker console. Click on the Create notebook instance button:
![](https://static.packt-cdn.com/products/9781787281066/graphics/assets/9d1fa78c-78c2-4223-accb-b1adc2255134.png)
- 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:
![](https://static.packt-cdn.com/products/9781787281066/graphics/assets/e2f54a68-fede-4ee7-a601-964dfda3478e.png)
- Select the Any S3 bucket option and click on the Create role button:
![](https://static.packt-cdn.com/products/9781787281066/graphics/assets/926b8261-37d1-470e-8a07-dacbfc26ebb0.png)
- Specify the Notebook instance name (as SageMakerTestNotebookInstance)...