SageMaker - Build, Train, and Deploy ML Model

If you have not set up an AWS Account (free tier can be used for SageMaker), please do so before continuing.

Step 1: Enter the Amazon SageMaker Console

Navigate to the Amazon SageMaker dashboard located in the left-hand panel and select Notebook Instances.
Select Create notebook instance button to begin creating the notebook instance.
Enter a name in the Notebook instance name field. Keep ml.t2.medium as the Notebook instance type.
An IAM role must be specified to enable the notebook instance to access and securely upload data to Amazon S3. In the IAM role field, choose Create a new role to have Amazon SageMkaer create a role with the required permissions and assign it to your instance.
In the Create an IAM role box, select Any S3 bucket. This allows your Amazon SageMkaer instance to access all S3 buckets in your account. For now, we will allow Any S3 bucket until we upload our our own bucket.
1. If you would like to clone our Git respository for your notebook instance, go to the Git repositories box and select Clone a public Git repository to this notebook instance only. Then insert "https://github.com/NaeRong/DS440_Capstone.git" in the Git repository URL box.
Choose Create role.
On the Notebook instances page, your new instance with your specified name should be shown with a Pending status. Your noteobok instance should transition from Pending to InService status in less than 2 minutes.