Set up and customize a basic pipeline for AI model training and inference on AWS.

This project demonstrates how to deploy an AI model on AWS SageMaker using a customized Docker image. It covers the entire workflow, including creating a training job, deploying an inference endpoint, and invoking predictions. The project also explores best practices for managing resources efficiently and separating model execution logic from the container image.

Detailed post: Basic pipeline for AI model training and inference on AWS.