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).
Make sure you start with the Quick start tutorial to understand the basics
Introduction to MLRun - Use serverless functions to train and deploy models
Targeted tutorials#
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#
See more examples in the end-to-end demos:
Cheat sheet#
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:
fraud-prevention-feature-store
network-operations
azureml_demo