This week we will continue our continuation of our MLOps series by looking at the pipeline approach for machine learning operations. We will complete the Kedro for the implementation framework and discuss other products and frameworks that provide a similar approach.
We will use our product recommendation project as a concrete example of building pipelines. By the end of the session, we will have the pipeline connected with GitHub actions to run the pipeline when changes are pushed to the repository. Included in this work will be a docker container definition for training the model published at DockerHub.