2.8. Data and prediction drift in ML [CODE PRACTICE]

A code example walkthrough of detecting data drift and creating a custom method for drift detection using Evidently.

Video 8. Data and prediction drift in ML [CODE PRACTICE], by Emeli Dral

In this video, we walk you through the code example of detecting data drift and creating a custom method for drift detection using the open-source Evidently Python library.

Want to go straight to code? Here is the example notebook to follow along.

Outline: 00:00 Create a working environment and import libraries 01:33 Overview of the data drift options 04:25 Evaluating share of drifted features 06:40 Detecting column drift 11:47 Set different drift detection method per feature type 12:57 Set individual different drift detection methods per feature 15:34 Custom drift detection method

Enjoyed the content?

Star Evidently on GitHub to contribute back! This helps us create free, open-source tools and content for the community.

⭐️ Star on GitHub!