Continuous Integration for ML applications - a practical example

Machine learning models are becoming obsolete and must be retrained - this is the current widespread tenor. After we have taken a closer look at this thesis, we will show how this can be done. Which components does a CI/CD pipeline for Machine Learning really need - and which are optional. How can the whole thing be implemented without building an entire ML Platform team. And which challenges are still difficult to solve.An experience report including (mis-)decisions that will help to take the right path with your own challenges. In addition, it gives an overview of the essential components of a functioning machine learning platform that focuses on solving business challenges through high automation and low vertical integration.