Tutorials and Examples
Tutorials and Examples#
The following tutorials provide a hands-on introduction to using MLRun to implement a data science workflow and automate machine-learning operations (MLOps).
Introduction to MLRun - Use serverless functions to train and deploy models
Each of the following tutorials is a dedicated Jupyter notebook. You can download them by clicking the
download icon at the top of each page.
End to end demos#
You can find the different end-to-end demos in the MLRun demos repository: github.com/mlrun/demos.
If you already know the basics, use the cheat sheet as a guide to typical use cases and their flows/SDK.
Running the demos in Open Source MLRun#
By default, these demos work with the online feature store, which is currently not part of the Open Source MLRun default deployment: