How to Build and Train a Model Using SageMaker and Artifactory

The following instructions will walk through the steps necessary to configure Artifactory and SageMaker in order to build and train an ML model.

A full working example of building and training an ML model using Tensorflow and the SageMaker Python SDK can be found in the train directory here.

The goal of this tutorial is to create, train, and store a model using SageMaker by performing the following steps:

1. Prepare a Python training script
2. Build a Docker container image for training
3. Create and store an ML model in Artifactory with a SageMaker training job