3 years ago

Category: Database, Data, Docker, github, shell, machine-learning

In this article, we will learn how to integrate Machine Learning models with DevOps using Jenkins and Docker. We know that training Machine Learning Models require a lot of RAM, and due to this reason it is nearly impossible to continuously test the models for accuracy. So to overcome this drawback we use a Docker environment to test our models and Jenkins for automating this task. Another thing that we can do, is to program Jenkins such that it detects the ML code and based on the code, Jenkins will use Docker to create a container environment.

This will first check the ML code and then it will start the container accordingly.Now we have to notify the admin about our Job, for this click on post build actions and click on editable Email and type in your Email address, but first configure Email Notification in Jenkins.