Databricks MLflow Tracking For Linear Regression Model

Author(s): Amy @GrabNGoInfo

Originally published on Towards AI.

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How to use MLflow to track different model versions and retrieve experiment information?

Photo by Solen Feyissa on Unsplash

MLflow is an open-source platform for machine learning lifecycle management. MLflow on Databricks offers an integrated experience for running, tracking, and serving machine learning models. In this tutorial, we will cover:

How to use MLflow to track different model versions?How to retrieve MLflow experiment information programmatically?How to retrieve MLflow information using Databricks UI?

Resources for this post:

Video tutorial for this post on YouTubeDatabricks notebook with codeMore video tutorials on Databricks and PySparkMore blog posts on Databricks and PySpark

Let’s get started!

In step 1, we will import… Read the full blog for free on Medium.

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Published via Towards AI