LAB | Train a Machine Learning Model in AWS SageMaker

Instructions

1. Log in to your AWS Console and navigate to SageMaker.

2. Inside SageMaker Studio:

   • Choose File → New → Notebook.
   • Select a small CPU kernel (e.g., Python 3).

3. Prepare your ML script:

   • You may reuse a previous ML model or create a new simple script.
   • Run code to train a model and make predictions.

4. When finished:

   • Go to Kernel → Shut Down to stop the notebook’s backing instance.
   • Make sure to stop the Notebook instance or delete to avoid incurring costs.
   • This ensures no further billing for infrastructure occurs.

Deliverable

• Screenshot of the Instance on AWS SageMaker.
• Screenshot of the notebook with the output of the prediction printed.

Submission

Upon completion, add your deliverables to git. Then commit git and push your branch to the remote.