Simple Model Retraining Automation via GitHub Actions

Easily streamline your modelling process with the GitHub Actions.

Photo by Praveen Thirumurugan on Unsplash

Machine Learning models could create immense value for the business. However, developing them isn’t a one-time activity. Instead, it’s a continuous process for the model to keep providing values. This is where MLOps came from.

The combination of CI/CD principles with machine learning development is what we call MLOps, which aims to provide continual value with the model.

One way for the Machine Learning model to bring constant benefit is by retraining them when necessary, for example, if the data drift is detected. We could perform the model retraining automation by setting the environment for retraining triggers.

We can use the GitHub tool called GitHub Actions to facilitate the retraining process. This tool is a feature from GitHub for the CI/CD platform used to automate the software development process from the GitHub repository.

This article will teach us how to perform model retraining automation controlled with the GitHub Actions. How to do that? Let’s get into it.

Preparation

We would perform a simple model development and automation demonstration for this project. The overall…