SageMaker is Amazon’s platform to build, train and deploy machine learning models quickly and at scale. And SageMaker Studio is the Integrated Development Environment (IDE) where you’ll be doing your work.
In this hands-on tutorial, I’ll walk you through how to create a SageMaker Domain and launch the SageMaker Studio app through the AWS Management Console. From there, I’ll show you how to launch a SageMaker solution for handwriting recognition, and then how to open and work in a Jupyter Notebook. Finally, and IMPORTANTLY, I’ll show you how to delete all SageMaker resources.
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– AWS Certified Cloud Practitioner: https://academy.zerotomastery.io/a/aff_n20ghyn4/external?affcode=441520_lm7gzk-d
– AWS Certified Solutions Architect Associate: https://academy.zerotomastery.io/a/aff_464yrtnn/external?affcode=441520_lm7gzk-d
You might also enjoy these other AWS videos:
• SageMaker Studio Lab: https://youtu.be/ue7LuQtE6Pw
• SageMaker Canvas: https://youtu.be/7v1-uQ0lCuQ
00:00 – Overviewing Amazon SageMaker
00:40 – Reviewing Amazon SageMaker Free Tier options and pricing
01:07 – Setting up a SageMaker Domain
02:02 – Launching Amazon SageMaker Studio
02:42 – Launching a SageMaker solution for handwriting recognition
06:04 – Opening and working in a Jupyter Notebook in a SageMaker solution
09:56 – IMPORTANT!! Deleting resources in a SageMaker solution