Conclusion¶

Congratulations! You did it! You were able to convert a ML experiment with a traditional approach to a well-defined, well-documented workflow that can scale and serve a model to the outside world!

Let's take the time to make a summary of what you have done.

Summary of what you have done¶

• The model can be reproduced

Thanks to DVC, the steps to create the model are documented and can be executed in order to reproduce the model.

• The changes done to a model can be tracked

Thanks to DVC, the changes done to a model can be tracked.

• The model can be used outside of the experiment context

Thanks to BentoML, the model can be served and be used outside of the experiment context.

Going further¶

This workshop has been developed for the AI Days@HES-SO 2025 Conference. It is a highly condensed version of our main MLOps course, which is available at mlops.swiss-ai-center.ch.

The main course goes much further and offers a more complete understanding of the subject, providing valuable knowledge and hands-on experience. We invite you to explore it for a deeper dive into MLOps.

Happy learning! :)