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.

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.

• Quick Start Tutorial
• Train, Compare, and Register Models
• Serving ML/DL models
• Projects and Automated ML Pipeline
• Feature store example (stocks)

You can find different end-to-end demos in MLRun demos repository at github.com/mlrun/demos. Alternatively, use the interactive MLRun Katacoda Scenarios that teach how to install and use MLRun.

• MLRun demos repository
• MLRun Katakoda Scenarios