Databricks MLflow — Python API — a few examples

This post is a previous one continuation: Databricks MLflow — manage models

Without further ado, here are a few examples of using MLflow Python API.

An easy way to remove a run or an experiment.

An all experiments list.

Detailed runs information.

A particular experiment details — by an ID.

By a name.

Particular run details.

A cool feature is an ability to use a [search_runs] function. If you want to list only particular set of runs.

Here are examples how to get URIs and last active run info during the run executing.

If you want to initiate mlflow as a new variable you create MlflowClient()

Here is a code: MLflow manage models