This repository contains the source code of the Machine Learning School program. Fork it to follow along.
If you find any problems with the code or have any ideas on improving it, please, open and issue and share your recommendations.
During this program we'll create a SageMaker Pipeline to build an end-to-end Machine Learning system to solve the problem of classifying penguin species.
Here are the relevant notebooks:
- The Setup notebook: We'll use this notebook at the beginning of the program to setup SageMaker Studio. You only need to go through the code here once.
- The Penguins in Production notebook: This is the main notebook we'll use during the program. Inside you'll find the code of every session.
- The Endpoint notebook: This notebook contains routines and examples to interact with a SageMaker Endpoint.
- The Monitoring notebook: This notebook contains the necessary code to configure and run data and model monitoring jobs.
- The Teardown notebook: You can use this notebook to remove some of the resources you created during the program.
During the program, you are encouraged to work on the Pipeline of Digits problem as the main assignment. To make it easier to start, you can use the Pipeline of Digits as a starting point.
- Serving a TensorFlow model from a Flask application: A simple Flask application that serves a multi-class classification TensorFlow model to determine the species of a penguin.