Amazon_Sagemaker

Deploy the ML model on Amazon Sagemaker

Steps

1. Login to AWS Console
2. Create a Notebook instance in the Sagemaker with this git repository.
3. Click on the 'Open Jupyter' to open the Jupyter console.
4. Open and Run the Notebook instance to
   • Create a s3 bucket
   • Download the data and save in the s3 bucket
   • train_test split to preprocess for the xGBoost
   • Implement xGBoost on the data
   • Create endpoint to expose the ML model
   • Delete the resources to save on billing

Note

1. Once you request to create a notebook instance, it'll take a decent 3-5 mins to set up the instance.